KR101613395B1

KR101613395B1 - Apparatus for detecting fluid leakage

Info

Publication number: KR101613395B1
Application number: KR1020150075222A
Authority: KR
Inventors: 이종민; 김연수; 박태균; 이신제; 서정철; 차헌주; 이기백
Original assignee: 주식회사 삼천리; 서울대학교산학협력단; 한국교통대학교산학협력단
Priority date: 2015-05-28
Filing date: 2015-05-28
Publication date: 2016-04-18

Abstract

A fluid leakage sensing device is provided. The fluid leakage detection device includes a data acquisition unit for acquiring pressure data of fluid, a data amplification unit for amplifying the degree of change of the pressure data using cumulative integration function to form cumulative data, And a leakage determination unit.

Description

[0001] APPARATUS FOR DETECTING FLUID LEAKAGE [0002]

The present invention relates to a fluid leakage sensing device.

As the city gets more complicated and the population grows, the lifeline that is essential for human life is also increasing. Among urban lifelines, pipelines have been used for a long time because they can transport most of the fluids such as water, oil, and gas. In addition, as industrialization is accelerating, large and small pipes installed in buildings are also being built to supply not only huge pipes installed underground but also various industries.

As such, pipes have been used in many areas for many years, so there are many cases of aging, and they are easily exposed to the outside environment, causing pipe leakage due to environmental changes and accidents. Leaks in pipelines transporting fluids important to human life, such as water and sewage pipes and oil pipelines, can not only cause enormous economic losses, but also can contaminate the underground environment.

CUSUM or MWA methods have been used to detect such fluid leaks. The above method can detect leakage and leakage position relatively easily when fluid leakage is large in scale. However, there is a disadvantage that it is difficult to detect if the fluid leakage is small. This is because, even if a change in pressure due to leakage occurs, it is difficult to discriminate whether the change is a pressure decrease due to use by the user or a pressure decrease due to leakage. Therefore, there is a problem that it is difficult to sensitively detect the fluid leakage by the conventional method.

In addition, it was possible to detect only the point where the leakage occurred in the past. However, the reliability is close to zero and may differ from the actual leak location. Because of such a problem, there is a problem that the length of the excavation becomes long to know where the leaking occurs, which is costly.

In order to solve the above problems, the present invention provides an apparatus for detecting a fluid leakage. The present invention provides an apparatus for detecting a position where a fluid leakage occurs.

Other objects of the present invention will become apparent from the following detailed description and the accompanying drawings.

A fluid leakage sensing apparatus according to embodiments of the present invention includes a data acquiring unit that acquires pressure data of a fluid, a data amplifying unit that accumulates accumulated data by amplifying a degree of change of the pressure data using a cumulative integration function, And a leakage determination unit for determining whether or not the leaked data is the accumulated data.

And a noise removing unit for removing the noise of the pressure data using a Kalman filter.

And a leak time confirmation unit for checking the occurrence time of the leakage using a curvature radius function.

The leakage determination unit may determine that the leakage data includes at least one of a step function, a floor function, a ceiling function, a unit step function, and a rectangular function, Can be used to form the deformed data.

The leakage determination unit may include a leak parameter calculation unit that calculates a leak parameter including the time Φ at which the fluid pressure is continuously reduced from the deformed data and the number of times N of the pressure decrease occurred.

The leakage determining unit may further include a variable determining unit for determining whether the Φ is less than or equal to a reference value Φ ₀ of the Φ, and determining whether the N is _greater than or equal to the reference value of N, N ₀ .

The fluid leakage sensing device includes a time data acquiring part for acquiring time data t _occ in a pressure sensor of a pipe for transporting a fluid, two of the pressure sensors as a reference sensor, s, and calculates a time t 'at which the leakage is sensed in the remaining sensors except for the reference sensor, and a time operation unit for comparing the t' and the t _occ, and comparing the sum of squares of the s As a leak prediction node s'.

The above-mentioned t _occ can be derived by using a curvature radius function.

And a leakage interval determination unit for deriving a leakage interval U including the s'.

The "the s contained in the setting section to set the interval U ₀ unit containing, and said U _0, the leakage section determination unit, and digging the excavation distance setting unit for setting the distance L, and the L or less, the s S (i) (i = 1, 2, ..., I), and sets one of the end points of U ₀ as an origin, and obtains a distance d 'between the S (i) and a leakage interval calculation unit for deriving the leakage interval U by using a confidence interval estimation method using d '

(mean of m _u = d ', Z = variance of standard normal random variable, σ' _U = d ') can be used.

L is the following formula

(k = conversion factor, L _element = pipe length).

The fluid leakage detection apparatus according to the embodiments of the present invention can detect leaks on the basis of the tendency of fluid leakage and detect a leakage of a small scale with a high probability. The fluid leakage detection device can detect a fluid leakage irrespective of the fluid leakage scale even in the presence of a lot of noise. Further, the fluid leakage detection apparatus can determine the position of the fluid leakage as a section using a statistical method. The fluid leakage detection device can derive the position of the fluid leakage in accordance with the actual situation. The fluid leakage sensing device may be directly applied to a system in which fluid leakage may occur.

1 is a fluid leakage sensing apparatus according to an embodiment of the present invention.
2 is a device for detecting a leakage of fluid according to an embodiment of the present invention.
3 is a leakage determination unit according to an embodiment of the present invention.
4 is a fluid leakage position sensing apparatus according to an embodiment of the present invention.
5 is a leakage section determination unit according to an embodiment of the present invention.
FIG. 6 is a method for detecting a fluid leakage according to an embodiment of the present invention.
7 is a flow leakage detection method according to an embodiment of the present invention.
8 is a leakage determination method according to an embodiment of the present invention.
9 is a method of sensing a fluid leakage interval according to an embodiment of the present invention.
10 is a method of determining a leak interval according to an embodiment of the present invention.
11 is a map of a water and sewage pipe of Youngwol in accordance with an embodiment of the present invention.
12 is initial pressure data of Youngwol in accordance with an embodiment of the present invention.
13 is leakage pressure data of Yeongwol according to an embodiment of the present invention.
FIG. 14 is pressure data from which noise is removed according to an embodiment of the present invention.
FIG. 15 shows data using a cumulative integration function according to an embodiment of the present invention.
FIG. 16 is a data obtained by applying a floor function according to an embodiment of the present invention.
FIG. 17 is data using a curvature radius function according to an embodiment of the present invention.
FIG. 18 shows a leakage position according to an embodiment of the present invention. FIG.

Hereinafter, the present invention will be described in detail with reference to examples. The objects, features and advantages of the present invention will be easily understood by the following embodiments. The present invention is not limited to the embodiments described herein, but may be embodied in other forms. The embodiments disclosed herein are provided so that the disclosure may be thorough and complete, and that those skilled in the art will be able to convey the spirit of the invention to those skilled in the art. Therefore, the present invention should not be limited by the following examples.

The leak detection apparatus and method according to embodiments of the present invention can effectively detect fluid leakage regardless of the size of the leaked fluid. Especially small-scale fluid leaks can be effectively detected. In another embodiment, the leak detection apparatus and method can detect an abnormal condition caused by an increase in pressure of a fluid. Further, in another embodiment, the leakage sensing apparatus and method can detect the point where the fluid leakage has occurred and / or the interval.

The fluid may be a liquid fluid or a gaseous fluid. In one embodiment, the pipe for transporting the fluid may be a water supply and drainage pipe, an oil pipe, or a gas pipe.

1 is a fluid leakage sensing apparatus 10 according to an embodiment of the present invention.

Referring to FIG. 1, the fluid leakage sensing device 10 may include a fluid leakage sensing device 100 and / or a fluid leakage sensing device 200. The fluid leakage detection device 100 can determine whether leakage has occurred in a pipe through which a fluid flows. If fluid leakage is detected in the pipe, the fluid leakage position sensing apparatus 200 can determine the position where the leakage occurred.

2 is an apparatus 100 for detecting a leakage of a fluid according to an embodiment of the present invention.

2, the fluid leakage detection apparatus 100 includes a data acquisition unit 110, a noise removal unit 120, a data amplification unit 130, a leakage determination unit 140, and / or a time verification unit 150).

The data acquiring unit 110 acquires pressure data of the fluid. The pressure data may be a value measured by the pressure sensor of the pipe or the tank, or may be an externally input value. The pipe may be a water pipe, a sewage pipe, an oil pipeline, a gas pipe, or the like. In one embodiment, the pressure data may be obtained at a pressure sensor present in the water supply and drainage pipe.

The noise removing unit 120 removes the noise of the pressure data using a Kalman filter. If the fluid leakage detection device 100 further includes the noise removing unit 120, noise such as a measurement error included in the pressure data obtained by the pressure sensor may be removed. The Kalman filter is an algorithm that can select a desired signal or information and is a probability based prediction system. The Kalman filter may include Equation (1).

Equation (1):

P [k] + P [k] = P [k] + w [k]

w ~ N (0, Q) , v ~ N (0, R), P [0] = C 0

(K) = the pressure at point k, w [k] = noise, z [k] = measured pressure, v [k] = measurement noise, covariance of Q = w [k] Covariance, C ₀ = covariance of Kalman filter initial value)

The data amplifying unit 130 amplifies the degree of change of the pressure data by using a cumulative integration function to form cumulative data. The pressure data may indicate a trend of pressure change when the leak occurs. It is possible to effectively determine whether the fluid leakage occurs through the tendency of the pressure change. In order to analyze the tendency of the pressure change, it is necessary to amplify the degree of change of the pressure data. The cumulative integral function can amplify the degree of change. Equation (2) and / or Equation (3) can be applied to the pressure data before using the cumulative integral function.

Equation (2):

(P _m = average pressure, P _{leak, e} = pressure data)

Equation (3):

(P _shift = converted value of the pressure data)

The P _shift is a converted value of the pressure data, and may indicate a degree of change of the pressure data. When the cumulative integral function is applied to the P _shift , the cumulative data in which the degree of change is amplified can be obtained. The cumulative integral function may be Equation (4).

Equation (4):

(P _CI = cumulative data, T = time)

The leak judging unit 140 judges whether or not the leakage data is leaked by using the accumulated data. When the fluid leakage has occurred, the cumulative data may include a trend of the pressure change. The tendency may be indicated by a time at which the pressure of the fluid is continuously reduced and / or a number of times at which the pressure decrease occurs, thereby determining whether the leakage is occurring. The transformed data may include at least one selected from the group consisting of a step function, a floor function, a ceiling function, a unit step function, and a rectangular function, Can be formed. In one embodiment, the floor function may be applied to the cumulative data, and the floor function may be equation (5).

Equation (5):

(P _floor = floor function)

The deformation data may be one in which the noise of the cumulative data is ignored. By using the deformation data, it is possible to efficiently determine whether or not the leakage occurs.

The time checking unit 150 can check the occurrence time of the leakage using the curvature radius function. The time verifying unit 150 can confirm the time at which the pressure change starts and / or the time at which the pressure change is started before or after determining whether the leakage occurs. The curvature radius function may be Equation (6).

Equation (6):

(radius of curvature data derived from three adjacent values of k [k] = curvature radius function, R [k] = P _CI )

3 is a leakage determination unit 140 according to an embodiment of the present invention.

Referring to FIG. 3, the leakage determination unit 140 may include a leakage parameter calculation unit 141 and / or a variable determination unit 142.

The leak parameter calculator 141 can calculate a leak parameter including the time Φ at which the fluid pressure is continuously reduced and the number of times N of the pressure decrease from the deformation data. The leaking parameter can be calculated using Equation (7).

Equation (7):

The variable determining unit 142 may sense the fluid leakage through the leakage variable. The variable determining unit 142 may detect leakage when the value of? Is _{equal to} or less than the reference value? _{0 of} ?, And when the value of N is _{equal to} or greater than N0 of the reference value of N. FIG. The Φ ₀ and N ₀ may be set in consideration of the size of the fluid leakage occurring. The Φ ₀ and N ₀ may be related to the sensitivity of the fluid leak detection system 10. The? ₀ may be 5 to 40 seconds. The N _o may be from 5 to 100. In one embodiment, the Φ ₀ is 20 seconds, the N ₀ may be 10 days.

4 is a fluid leakage position sensing apparatus 200 according to an embodiment of the present invention.

4, the fluid leakage position sensing apparatus 200 may include a time data acquisition unit 210, a time calculation unit 220, a leakage node calculation unit 230, and / or a leakage interval determination unit 240 have.

The time data acquiring unit 210 acquires the sensor time t _occ at which the leak is measured in the pressure sensor of the pipe that transports the fluid. The _tcsc may be obtained according to the user's input and / or settings. Preferably, tc _oc can be derived using the curvature radius function. The curvature radius function may be Equation (6).

Equation (6):

By using the curvature radius function, the time at which the leak is measured can be derived accurately. The _toc may be more than one per the pressure sensor in which the leak is sensed.

The time calculator 220 sets two of the pressure sensors as a reference sensor and sets a node s of the pipe close to the reference sensor to calculate a time t 'at which the leakage is detected in the remaining sensors except for the reference sensor . The reference sensor may be set to a number of _n C ₂ cases. The s may be set to one or more selected from Dijkstra Algorithm, Floyd's Algorithm, and Prim's Algorithm. And s may be a node located at a shortest distance from the reference sensor. The s may be set for each number of the reference sensors. The time at which the change in the pressure due to the fluid leakage to the pressure sensor reaches the node when the fluid leak has occurred at the node may be proportional to the distance between the node and the pressure sensor. The occurrence time t _{occ, s} of the leakage in the _s can be calculated using the distance between the reference sensor and the s and the t _{c oc} in the reference sensor. The above-mentioned t _{occ, s} can be derived using the equation (8).

Equation (8):

(d _is = distance between reference sensor i and node s, d _js = distance between reference sensor j and node s, t _{i, basis} = t _occ , t _{j, basis of} reference sensor i t _occ , t _{occ, s} = leak occurrence time at node s)

Using t _{occ, s} , a change in the pressure due to the fluid leakage can elicit a time t 'at which the leak is sensed by the remaining sensor except for the reference sensor. If the remaining sensor is denoted by l, the time at which the leakage is detected in the _l may be t ' _l . Equation (9) can be used to calculate t '.

Equation (9):

(d _ls = distance between pressure sensor l and node s, t ' _l = t' at pressure sensor l)

Said t _'l may be derived for each dog n-2 number of cases of the reference sensor.

The leakage node arithmetic unit 230 compares t 'and t _occ and determines s as the leak prediction node s' that the sum of the square of the error is minimum. Preferably, the difference s between the t ' ₁ and the t' s in the l is _regarded as an error, and the sum s of the sum of the error squares is determined as s'. The above s' can be derived by equation (10).

Equation (10):

(S (s) = sum of error squares, t _{l, obs} = t _occ at pressure sensor l)

The J (s) may be one or more. Wherein s' may be greater than or equal to ₂ _n C. The s' may be displayed on a map interface such as a GIS (Geographic Information System) and provided to a user.

5 is a leakage interval determination unit 240 according to an embodiment of the present invention.

5, the leak interval determination unit 240 may include a drilling distance setting unit 241, a section setting unit 242, a distance calculating unit 243, and / or a leak interval calculating unit 244. [ The leak interval determination unit 240 can determine the position of the fluid leakage as a section rather than a point (node), and thus the reliability is high.

The excavation distance setting unit 241 sets the excavation distance L. The L may be a maximum length that can confirm the position of the pipe where the fluid leakage occurs. The L may vary depending on the characteristics of the excavation equipment, the distance that can be drilled cost-effectively, and / or the length of the installed pipe. L can be derived using equation (11).

Equation (11):

(k = conversion factor, L _element = pipe length)

K is a conversion factor, preferably 1 or more.

The interval setting unit 242 sets the interval U ₀ , which is _equal to or smaller than L, and includes s'. U ₀ may be a period including the most s'. In one embodiment, if several U ₀ are derived, the shortest U ₀ can be selected.

The distance calculator 243 sets s' included in U ₀ as S (i) (i = 1, 2, ..., I), sets one of the end points of U ₀ as the origin, i and the distance d 'between the origin points. The I is the number of s' included in the U ₀ .

The leak interval calculator 244 derives the leak interval U as a confidence interval estimating method using d '. The leak interval calculator 244 can derive the fluid leak interval U with higher reliability than U ₀ by the confidence interval estimating method. The confidence interval estimation method may be Equation (12).

Equation (12):

(mean of m _u = d ', Z = variance of standard normal random variable, σ' _U = d ')

The U may be displayed on a map interface such as a GIS (Geographic Information System) and provided to a user.

When the s' not included in the U is s' ₀ , the s' ₀ may have a high probability of the fluid leakage. In one embodiment, the user may take additional measures to prevent the occurrence of the fluid leakage with respect to s' ₀ .

6 is a fluid leakage detection method (S10) according to an embodiment of the present invention.

Referring to FIG. 6, the fluid leakage detection method (S10) may include a fluid leakage detection method (S100) and / or a fluid leakage position sensing method (S200). It is possible to determine whether or not leakage has occurred in the pipe through which the fluid flows, by the fluid leakage detection method (S100). When the fluid leakage is detected in the pipe, the fluid leakage position sensing method (S200) can determine the location of the leakage.

FIG. 7 is a method S100 for detecting whether a fluid is leaked according to an embodiment of the present invention.

Referring to FIG. 7, the fluid leakage detection method S100 includes obtaining fluid pressure data (S110), removing noise of the pressure data using a Kalman filter (S120), using a cumulative integral function (S140), and / or a leak time checking step (S150). The leakage determination step (S140) includes determining whether the fluid is leaking from the accumulated data .

And obtains pressure data of the fluid (S110). The pressure data may be a value measured by the pressure sensor of the pipe or the tank, or may be an externally input value. The pipe may be a water pipe, a sewage pipe, an oil pipeline, a gas pipe, or the like. In one embodiment, the pressure data may be obtained at a pressure sensor present in the water supply and drainage pipe.

The noise of the pressure data is removed using a Kalman filter (S120). If the method further includes a step of removing noise (S120) in the fluid leakage detection method (S100), noise such as a measurement error included in the pressure data acquired by the pressure sensor may be removed. The Kalman filter is an algorithm that can select a desired signal or information and is a probability based prediction system. The Kalman filter may include Equation (1).

Equation (1):

P [k] + P [k] = P [k] + w [k]

w ~ N (0, Q) , v ~ N (0, R), P [0] = C 0

In the step of forming the cumulative data (S130), cumulative data is formed by amplifying the degree of change of the pressure data by using the cumulative integral function. The pressure data may indicate a trend of pressure change when the leak occurs. It is possible to effectively determine whether the fluid leakage occurs through the tendency of the pressure change. In order to analyze the tendency of the pressure change, it is necessary to amplify the degree of change of the pressure data. The cumulative integral function can amplify the degree of change. Equations (2) and (3) can be applied to the pressure data before using the cumulative integral function.

Equation (2):

(P _m = average pressure, P _{leak, e} = pressure data)

Equation (3):

(P _shift = converted value of the pressure data)

Equation (4):

(P _CI = cumulative data, T = time)

In the leakage determination step (S140), it is determined whether leakage is occurred using the accumulated data. When the fluid leakage has occurred, the cumulative data may include a trend of the pressure change. The tendency may be indicated by a time at which the pressure of the fluid is continuously reduced and / or a number of times at which the pressure decrease occurs, thereby determining whether the leakage is occurring. The transformed data may include at least one selected from the group consisting of a step function, a floor function, a ceiling function, a unit step function, and a rectangular function, Can be formed. In one embodiment, the floor function may be applied to the cumulative data, and the floor function may be equation (5).

Equation (5):

(P _floor = floor function)

In the leakage time confirmation step S150, the occurrence time of the leakage can be confirmed using the curvature radius function. The leak time confirmation step (S150) may be performed before or after determining whether or not the leakage occurs, and the time at which the pressure change starts and / or the time at which the pressure change is started can be confirmed. The curvature radius function may be Equation (6).

Equation (6):

By using the curvature radius function, the leakage time can be elaborately derived. The leak time may be more than one per the pressure sensor in which the leak was detected.

8 is a leakage determination method (S140) according to an embodiment of the present invention.

Referring to FIG. 8, the leakage determination method (S140) includes a leakage parameter calculation step S141 including? And N, and / or a variable determination step S142 for detecting the leakage according to the criterion .

In the leakage parameter calculation step (S141), it is possible to calculate a leakage parameter including the time Φ at which the fluid pressure is continuously reduced from the deformed data, and the number of times N of the pressure reduction occurred. The leaking parameter can be calculated using Equation (7).

Equation (7):

In the variable determining step S142, the fluid leakage may be detected using the leakage parameter. In the variable discrimination step (S142), wherein Φ is the can to determine if Φ ₀ Φ greater than the value for the reference, and if greater than or equal to the N N ₀ is the reference value of said N detected leakage. The Φ ₀ and N ₀ may be set in consideration of the size of the fluid leakage occurring. The Φ ₀ and N ₀ may be related to the sensitivity of the method the fluid leakage detected (S10). The? ₀ may be 5 to 40 seconds. The N _o may be from 5 to 100. In one embodiment, the Φ ₀ is 20 seconds, the N ₀ may be 10 days.

9 is a method (S200) for sensing a fluid leakage position according to an embodiment of the present invention.

Referring to FIG. 9, the fluid leakage position sensing method S200 includes a time data acquisition step 210, a time calculation step S220, a leak node determination step S230, and / or a leak interval determination step S240 .

In the time data acquisition step (S210), the sensor time t _occ at which leakage has been measured is obtained at the pressure sensor of the pipe carrying the fluid. The above-mentioned t _occ can be derived by using a curvature radius function. The curvature radius function may be Equation (6).

Equation (6):

In the time computing step S220, two of the pressure sensors are set as a reference sensor, a node s of the pipe close to the reference sensor is set, and the remaining sensor excluding the reference sensor detects a time t '. The reference sensor may be set to a number of _n C ₂ cases. The s may be set to one or more selected from Dijkstra Algorithm, Floyd's Algorithm, and Prim's Algorithm. And s may be a node located at a shortest distance from the reference sensor. The s may be set for each number of the reference sensors. The time at which the change in the pressure due to the fluid leakage to the pressure sensor reaches the node when the fluid leak has occurred at the node may be proportional to the distance between the node and the pressure sensor. The occurrence time t _{occ, s} of the leakage in the _s can be calculated using the distance between the reference sensor and the s and the t _{c oc} in the reference sensor. The above-mentioned t _{occ, s} can be derived using the equation (8).

Equation (8):

Equation (9):

In the leak node judgment step (S230), t 'and t _occ are compared and the value of s, which is the sum of the square of the error, is determined as the leak prediction node s'. Preferably, the difference s between the t ' ₁ and the t' s in the l is _regarded as an error, and the sum s of the sum of the error squares is determined as s'. The above s' can be derived by equation (10).

Equation (10):

(S (s) = sum of error squares, t _{l, obs} = t _occ at pressure sensor l)

10 is a method of determining a leak interval (S240) according to an embodiment of the present invention.

Referring to FIG. 10, the leak interval determination method S240 may include a drilling distance setting step S241, a section setting step S242, a distance calculating step S243, and / or a leak interval calculating step S244. have. If the leakage interval determination method (S240) is used, the position of the fluid leakage can be determined as a section rather than a point (node), and the reliability is high.

In the excavation distance setting step S241, the excavation distance L is set. The L may be a maximum length that can confirm the position of the pipe where the fluid leakage occurs. The L may vary depending on the characteristics of the excavation equipment, the distance that can be drilled cost-effectively, and / or the length of the installed pipe. L can be derived using equation (11).

Equation (11):

(k = conversion factor, L _element = pipe length)

K is a conversion factor, preferably 1 or more.

In the section setting step S242, a section U ₀ that is _equal to or smaller than L and includes s' is set. U ₀ may be a period including the most s'. In one embodiment, if several U ₀ are derived, the shortest U ₀ can be selected.

In step S243, the s' included in the U ₀ is defined as S (i) (i = 1, 2, ..., I), one of the end points of U ₀ is set as the origin, S (i) and the distance d 'between the origin points. The I is the number of s' included in the U ₀ .

In the leakage interval calculation step S244, the leakage interval U is derived by the confidence interval estimation method using d '. In the leakage interval calculation step S244, the fluid leakage interval U having higher reliability than U ₀ can be derived by the confidence interval estimation method. The confidence interval estimation method may be Equation (12).

Equation (12):

[Example]

The purpose of this experiment is to determine if the leak detection apparatus and method according to an embodiment of the present invention can effectively detect small-scale leaks, and other additional functions and effects can also be described.

11 is a map of a water and sewage pipe of Youngwol in accordance with an embodiment of the present invention.

Referring to FIG. 11, the pipes of water and sewage pipes in Yeongwol, Gangwon-do, Korea, which is one embodiment of the present invention, have a total length of 7266.4356 m and have 861 nodes. The position of the pressure sensor (Sensor Location) is six.

For the experiment, an artificial fluid leak was generated using a hydrant in the water supply and sewerage, and the leakage location is shown in FIG.

Fluid leak detection

12 is initial pressure data of Youngwol in accordance with an embodiment of the present invention. 13 is leakage pressure data of Yeongwol according to an embodiment of the present invention.

Referring to FIG. 12, the pressure (kPa) data according to the transverse time (Time [s]) is shown for each of the six pressure sensors. The initial pressure data of FIG. 12 may correspond to the initial pressure data, which is generated by using the hydrant.

Referring to FIG. 13, in order to realize the leakage of the small scale, the scale of the data of FIG. 12 is shown in a reduced scale. The pressure data in FIG. 13 may represent a small scale leak.

FIG. 14 is pressure data from which noise is removed according to an embodiment of the present invention.

Referring to FIG. 14, the result of removing the noise of the pressure data by applying the Kalman filter according to an embodiment of the present invention is shown.

FIG. 15 shows data using a cumulative integration function according to an embodiment of the present invention.

Referring to FIG. 15, the cumulative data in which the continuous change of the pressure data is amplified by applying the cumulative integral function according to an embodiment of the present invention is shown. The equations (2) and (3) can be applied to the pressure data before applying the cumulative integral function.

Equation (2):

(P _m = average pressure, P _{leak, e} = pressure data)

Equation (3):

(P _shift = converted value of the pressure data)

The data derived from the above equations (2) and (3) can be applied to the above equation (4).

Equation (4):

(P _CI = cumulative data, T = time)

The cumulative data shows the tendency of the pressure decrease due to the leakage of the fluid.

FIG. 16 is a data obtained by applying a floor function according to an embodiment of the present invention.

Referring to FIG. 16, the transformed data in which unnecessary noise of the accumulated data is removed by applying a floor function according to an embodiment of the present invention is shown. The modified data can be derived by applying Equation (5) to the cumulative data.

Equation (5):

(P _floor = floor function)

By using the deformation data, the cause of the fluid leakage can be inferred. In the present embodiment, it can be confirmed that the pressure decreasing tendency of the sensor 1, the sensor 2, the sensor 3, the sensor 5, and the sensor 6 is different from the pressure decreasing tendency of the sensor 4. The cause of the pressure decrease of the sensor 4 may be different from the other sensors.

The Cusp point of the deformation data can be used to analyze the pressure drop tendency. In the variant data, the point of intersection may be the point at which sudden pressure reduction is found. From the deformation data, it is possible to calculate a leakage parameter that includes a time Φ at which the pressure of the fluid is continuously reduced, and a number of times N in which the pressure reduction occurs. The leaking parameter can be calculated using Equation (7).

Equation (7):

If the Φ and the N are derived for each sensor, the leakage of the fluid can be determined by comparing the Φ and the reference value. If Φ is less than if the reference value or less of the Φ ₀ Φ, and said N is N ₀ is the value for the reference N, it can be judged as leakage. In this embodiment, the Φ ₀ is 20 seconds, the N ₀ was set at 10. In the present embodiment, as a result of determining whether the leakage is leaking, the remaining sensor except for the sensor 4 has the Φ of 20 seconds or less and the N of 10 or more. As a result of the leakage of the fluid, Respectively.

The curvature radius function may be used to precisely identify the time at which the fluid leakage occurs.

Sensor 1 Sensor 2 Sensor 3 Sensor 4 Sensor 5 Sensor 6 Time (seconds) 207.68 201.00 202.44 - 204.44 204.08

Sensor 1 Sensor 2 Sensor 3 Sensor 4 Sensor 5 Sensor 6 Time (seconds) 197.80 197.32 196.68 - 197.60 196.60

Table 1 shows the pressure reduction start time of the deformation data. 17 and Table 2 are data to which a curvature radius function is applied according to an embodiment of the present invention.

Referring to Tables 1, 2, and 17, it can be seen that the data of Table 2 to which the curvature radius function of FIG. 17 is applied represents the leakage time which is relatively accurate as compared with Table 1.

Fluid Leak Position Detection

In order to sense the fluid leakage position, a sensor time _t.sub.cc was measured at which leakage was measured at the pressure sensor of the pipe carrying the fluid. In the present embodiment, t _occ is derived by using a curvature radius function. The curvature radius function may be Equation (6).

Equation (6):

Two of the pressure sensors are set as a reference sensor, and a node s of the pipe near the reference sensor is set, and the time t 'at which the leakage is sensed by the remaining sensors excluding the reference sensor is calculated. The reference sensor may be set to a number of _n C ₂ cases. In this embodiment, since the fluid leaks were detected in the five sensors, the reference sensor was generated in the number of cases of ₅ C ₂ (10 kinds) instead of ₆ C ₂ . In the present embodiment, s is set to a Dijkstra Algorithm. In the present embodiment, ten s have been derived.

The occurrence time t _{occ, s} of the leakage in the _s can be calculated using the distance between the reference sensor and the s and the t _{c oc} in the reference sensor. In this embodiment, t _{occ, s} is derived using the following equation (8).

Equation (8):

Using t _{occ, s} , a change in the pressure due to the fluid leakage can elicit a time t 'at which the leak is sensed by the remaining sensor except for the reference sensor. If the remaining sensor is denoted by l, the time at which the leakage is detected in the _l may be t ' _l . In this embodiment, equation (9) is used to calculate t '.

Equation (9):

Said t _'l may be derived for each dog n-2 number of cases of the reference sensor. In the present embodiment, t ' ₁ is derived for each of the reference sensors.

T 'is compared with _tcoc , and the value of s, which is the sum of the square of the error, is determined as the leak prediction node s'. In the present embodiment, the difference between t ' ₁ and t _occ in l is _regarded as an error, and the value s, which is the sum of the square of the error, is determined as s'. In the present embodiment, s' is derived by equation (10).

Equation (10):

(S (s) = sum of error squares, t _{l, obs} = t _occ at pressure sensor l)

In this embodiment, ten s' are derived. In another embodiment, the minimum value may be derived several times, so that s' can be at least _n C ₂ .

FIG. 18 shows a leakage position according to an embodiment of the present invention.

Referring to FIG. 18, s' is represented by a red dot, and U is estimated to have a reliability of 90%, and is represented by a blue band (Interval Estimation with confidence level of 90%).

In order to derive the leakage section U, the excavation distance L was set. The L may be a maximum length that can confirm the position of the pipe where the fluid leakage occurs. The L may vary depending on the characteristics of the excavation equipment, the distance that can be drilled cost-effectively, and / or the length of the installed pipe. In this embodiment, L is derived using the following equation (11).

Equation (11):

(k = conversion factor, L _element = pipe length)

K is a conversion factor, preferably 1 or more.

In this embodiment, k was 1, L _element was 400 m, and L was set to 400 m.

And the interval U ₀ , which is _equal to or smaller than L, and includes s'. U ₀ may be a period including the most s'. In the present embodiment, U ₀ is set to a section including seven s' s shown on the right side of FIG.

S (i) included in U ₀ is defined as S (i) (i = 1, 2, ..., I) and one of the end points of U ₀ is set as the origin, Is obtained. The I is the number of s' included in the U ₀ . In this embodiment, I is 7.

The leakage interval U is derived from the confidence interval estimation method using d '. In the present embodiment, the confidence interval estimation method uses the following equation (12).

Equation (12):

In the present embodiment, when the reliability is determined as 90%, the Z is set to 1.65. In another embodiment, when the reliability is 95%, Z may be 1.96. In another embodiment, when the reliability is 99%, Z may be 2.58.

It is possible to derive the U using the length derived by the confidence interval estimation method. In this embodiment, U is represented by a blue band in Fig. The user can excavate the U section having the highest fluid leakage probability to reduce the cost of the excavation.

When the s' not included in the U is s' ₀ , the s' ₀ may have a high probability of the fluid leakage. In this embodiment, the user can take measures to prevent the occurrence of the fluid leakage with respect to the positions 5, 7, 10 and the right 1, 6, 4, 9 positions in FIG. 18 corresponding to s' ₀ .

Hereinafter, specific embodiments of the present invention have been described. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

10: Fluid leakage detection device 100: Fluid leakage detection device
110: data acquisition unit 120: noise rejection unit
130: data amplification unit 140: leak determination unit
141: Leakage Variable Operation Unit 142: Variable Determination Unit
150: leak time confirmation unit 200: fluid leakage position detection device
210: time data acquisition unit 220: time calculation unit
230: Leak node computing unit 240: Leakage period determining unit
241: Excavation distance setting unit 242:
243: Distance calculation unit 244: Leakage interval calculation unit
S10: Fluid leakage detection method S100: Fluid leakage detection method
S110: Pressure data acquisition step S120: Noise removal step
S130: cumulative data formation step S140: leak determination step
S141: Leakage Variable Operation Step S142: Variable Judgment Step
S150: leak time confirmation step S200: fluid leakage position detection method
S210: Time data acquisition step S220: Time calculation step
S230: Leak node determination step S240: Leakage section determination step
S241: Excavation distance setting step S242:
S243: Distance calculation step 244: Leakage interval calculation step

Claims

A data obtaining unit obtaining pressure data of the fluid;
A data amplifying unit for amplifying the degree of change of the pressure data by using a cumulative integral function to form cumulative data; And
And a leakage determination unit for determining whether or not the leaked data is the accumulated data,
The leakage determination unit
The transformed data may include at least one selected from the group consisting of a step function, a floor function, a ceiling function, a unit step function, and a rectangular function, Lt; / RTI >
From the deformation data, a leakage parameter calculation unit which calculates a leakage parameter including a time? During which the pressure of the fluid is continuously reduced and a number of times N in which the pressure reduction occurs.

The method according to claim 1,
And a noise removing unit for removing noise of the pressure data using a Kalman filter.

The method according to claim 1,
And a leakage time checking unit for checking the occurrence time of the leakage using a curvature radius function.

delete

The method according to claim 1,
The leakage determination unit
Further comprising a variable determining unit for determining whether the Φ is less than or equal to a reference value Φ ₀ of the Φ, and determining whether the N is _greater than or equal to the reference value of N, N ₀ .

A data obtaining unit obtaining pressure data of the fluid;
A data amplifying unit for amplifying the degree of change of the pressure data by using a cumulative integral function to form cumulative data;
A leakage judging unit for judging whether or not leakage occurs by using the accumulated data;
A time data acquiring unit for acquiring a sensor time t _occ at which leakage is measured in a pressure sensor of a pipe that transports the fluid;
A time arithmetic unit for setting two of the pressure sensors as a reference sensor, setting a node s of the pipe near the reference sensor, and calculating a time t 'at which the leak is sensed by the remaining sensors except for the reference sensor; And
And a leakage node determiner for comparing the t 'and the _tcoc and determining the s as the leak predicted node s' where the sum of squares of the errors is minimum.

8. The method of claim 7,
_{Wherein the tcr} is derived using a curvature radius function.

8. The method of claim 7,
And a leakage interval determination unit for deriving a leakage interval U including the s'.

10. The method of claim 9,
The leakage section determination unit may determine,
An excavation distance setting unit for setting excavation distance L;
A section setting unit for setting a section U ₀ , which is _equal to or smaller than L, including the s'; And
S (i) included in U ₀ is defined as S (i) (i = 1, 2, ..., I) and one of the end points of U ₀ is set as the origin, A distance calculating unit for calculating a distance d ' And
And a leakage interval calculation unit for deriving the leakage interval U by using the confidence interval estimation method using d '
The confidence interval estimating method is based on the following equation

(mean of m _u = d ', Z = variance of standard normal random variable, σ' _U = d ').

11. The method of claim 10,
L is the following formula

(k = conversion factor, L _element = pipe length). < / RTI >