CN105927863A - DMA zone pipe network leakage online detecting and positioning system and detecting and positioning method thereof - Google Patents

Abstract

The invention relates to the technical field of tap water supply pipe network leakage measurement, in particular to a DMA zone pipe network leakage online detecting and positioning system and a detecting and positioning method thereof. The system comprises a DMA zone tap water main pipeline, a first DMA zone tap water branch pipeline, a second DMA zone tap water branch pipeline,..., an N-1<th> DMA zone tap water branch pipeline, an N<th> DMA zone tap water branch pipeline, a data collecting unit, pressure detecting units, sound wave detecting units, a system server and a work station. The data collecting unit is installed on the tap water main pipeline in the position of an inlet of a DMA zone, and data are uploaded to the system server through a GPRS/3G/4G module. The pressure detecting units or the sound wave detecting units, or the pressure detecting units and the sound wave detecting units are installed on the first DMA zone tap water branch pipeline, the second DMA zone tap water branch pipeline,..., the N-1<th> DMA zone tap water branch pipeline and the N<th> DMA zone tap water branch pipeline correspondingly, and the pressure detecting units and the sound wave detecting units upload data to the system server through the GPRS/3G/4G module. The system server communicates with the work station through the industrial Ethernet. The DMA zone pipe network leakage online detecting and positioning system and the detecting and positioning method thereof are suitable for underground water supply pipe networks, installation is easy, and leakage detecting and positioning of terminal pipeline networks of all the urban DMA zones are well achieved.

Description

DMA subregion pipeline network leak on-line checking alignment system and detection and location method thereof

Technical field

The present invention relates to a kind of DMA subregion pipeline network leak on-line checking alignment system and detection and location method thereof, Belong to tap water supply pipe network to leak hunting technical field.

Background technology

It is that warp improves in urban water supply company that public supply mains are revealed " the non-income water rate " caused high The major obstacles of Ji benefit.Public supply mains leakage is mostly derived from the magnanimity of the little leak point of water supply network end Reveal accumulation.If the most accurately detecting, positioning the leak point of public supply mains, it will make to water resource Become waste greatly.

Along with the development of modern city, the optimization of public supply mains is transformed with decoupling, is carried out reasonable DMA Subregion is common recognition and the development trend of Urban water supply.Water system pipe network independent measure subregion (DMA) Reasonably optimizing construction and upgrading are to simplify pipe network topology, balance pipe network load, raising water supply security and strengthening to supply Water system monitoring and the only way which must be passed of management level.

Summary of the invention

For the problem overcoming prior art to exist, the present invention proposes a kind of DMA subregion pipeline network leak and examines online Surveying alignment system and detection and location method thereof, this system is suitable for groundwater supply pipe network environment, is easily installed, becomes This is cheap, solves leak diagnostics and the orientation problem of public supply mains DMA subregion end pipe network well, Leakage point can be detected in time, decrease a large amount of losses of water resource.

In order to realize foregoing invention purpose, the technical solution used in the present invention is: a kind of DMA subregion pipe network is let out Leakage on-line checking alignment system, including DMA subregion tap water main line, DMA subregion the 1st, 2 ... N-1, N tap water bye-pass, data acquisition unit, pressure sensing cell, sonic detection unit, system server and Work station, described data acquisition unit, including pressure transducer, flow transducer and data acquisition RTU module, Wherein pressure transducer, flow transducer are arranged on the tap water main line of DMA subregion porch, data Gather RTU module be arranged on the borehole wall of adjacent valve well, described pressure transducer, flow transducer respectively with In data acquisition RTU module, two RS-485 interfaces are connected, for collecting DMA subregion porch Pressure on tap water main line, data on flows are by being built in the GPRS/3G/4G of data acquisition RTU module Module by timing or real-time in the way of data are uploaded to system server；Described DMA subregion the 1st, 2 ... N-1, On N tap water bye-pass, it is separately installed with pressure sensing cell or sonic detection unit or pressure according to field working conditions Power detector unit and sonic detection unit, described pressure sensing cell, including being arranged on DMA subregion tap water Pressure transducer on bye-pass and the data acquisition RTU module being arranged on the borehole wall of adjacent valve well, described Sonic detection unit, including the pipeline sonic transducer being arranged on DMA subregion tap water bye-pass and be arranged on Data acquisition RTU module on the borehole wall of adjacent valve well, described pressure transducer, pipeline sonic transducer are respectively It is connected with RS-485 interface in data acquisition RTU module, for the tap water that will collect in DMA subregion Pressure on bye-pass and sonic data by be built in the GPRS/3G/4G module of data acquisition RTU module with Data are uploaded to system server by timing or real-time mode, by industry between system server and work station Ethernet carries out communication；Described work station, including data collection control unit, statistical model parameter calculation unit, Leak hunting positioning unit and DMA partition monitor of pipe network diagnosis unit, sound characteristics computational analysis unit, leakage point shows Show unit, wherein, described data collection control unit, also include gathering target configuration subelement, data acquisition Pattern configurations subelement, data transmit-receive and communications protocol resolve subelement, real-time database data management subelement, go through History bank interface subelement and located in connection data acquisition Collaborative Control subelement, based on data acquisition unit, pressure The data that detector unit and sonic detection unit gather, through statistical model parameter calculation unit and pipe network diagnosis unit Jointly completing judgement and the judgement in leakage orientation that whether pipeline network leak exists, sound characteristics computational analysis unit completes Judged that the pipeline sonic data leaking around orientation calculates.

The detection and location method of described a kind of DMA subregion pipeline network leak on-line checking alignment system, including following Step:

Step 1, set up DMA water rationing pipe network operation state rule statistical models, described statistical models Setting up premise is that pipeline is properly functioning and No leakage, according to actual condition, is divided into n time period by 24 hours, Have 1 flow monitoring point, p pressure monitoring point in DMA subregion, specifically include following sub-step:

A in () single time period, in DMA subregion entry data collecting unit, flow transducer gathers m DMA Subregion tap water main line data on flows, gathers 1 data on flows every time, and each data on flows all includes this stream The acquisition time of amount data, finds the maximum max of data on flows in this time period₁And minima min₁, peak-to-peak Value P₁It is calculated by formula (1),

P₁=max₁-min₁(1)

The meansigma methods of DMA subregion tap water main line data on flows in this time periodCalculated by formula (2) Obtain,

${\stackrel{\&OverBar;}{X}}_1=\frac{1}{m}\underset{i=1}{\overset{m}{\&Sigma;}}{X}_i---\left(2\right)$

In formula, the DMA subregion tap water total number of main line data on flows that m gathers in representing this time period, X_i Represent the i-th data in m DMA subregion tap water main line data on flows, single time in this time period The variance yields s of DMA subregion tap water main line data on flows in section₁ ²It is calculated by formula (3),

${s_1}^2=\frac{1}{m-1}\underset{i=1}{\overset{m}{\&Sigma;}}{(X_i-{\stackrel{\&OverBar;}{X}}_1)}^2---\left(3\right)$

M-discharge model when () sets up b, duplicon step (a) n time, in calculating respectively one day during n difference Between DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods and variance yields, first record the 1st in section DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods and variance yields in the individual time period, and with stream Amount data and the corresponding relation of this data acquisition time, with the time as transverse axis, in this time period, DMA subregion enters The data on flows of mouth data acquisition unit flow transducer is that the longitudinal axis sets up curve, i.e. sets up model Q₁, then with DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods and variance yields in 2nd time period, and With the corresponding relation of data on flows Yu this data acquisition time, with the time as transverse axis, in this time period, DMA divides The data on flows of district's entry data collecting unit flow transducer is that the longitudinal axis sets up curve, i.e. sets up model Q₂, depend on This analogizes DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods and side in the n-th time period of record Difference, and with the corresponding relation of data on flows Yu this data acquisition time, with the time as transverse axis, in this time period The data on flows of DMA subregion entry data collecting unit flow transducer is that the longitudinal axis sets up curve, i.e. sets up model Q_n, according to the change dynamic corrections above-mentioned model Q of data₁～Q_n；

C in () single time period, in pressure sensing cell, pressure transducer gathers k pressure at single pressure monitoring point Force data, gathers 1 pressure data every time, and each pressure data all includes the acquisition time of this pressure data, So within the single time period, single monitoring point gathers pressure data k altogether, finds number pressure in this time period According to maximum max₂And minima min₂, peak-to-peak value P₂Obtained by formula (4),

P₂=max₂-min₂ (4)

The meansigma methods of single pressure monitoring point pressure dataIt is calculated by formula (5),

${\stackrel{\&OverBar;}{X}}_2=\frac{1}{k}\underset{j=1}{\overset{k}{\&Sigma;}}{X}_j---\left(5\right)$

In formula, the k total number of pressure data that in representing this time period, single pressure monitoring point gathers, X_jWhen representing this Between in section in jth data, single pressure monitoring point number pressure in the pressure data that gathers of single pressure monitoring point According to variance yields s₂ ²It is calculated by formula (6),

${s_2}^2=\frac{1}{k-1}\underset{j=1}{\overset{k}{\&Sigma;}}{(X_j-{\stackrel{\&OverBar;}{X}}_2)}^2---\left(6\right)$

D () duplicon step (c) p time, in calculating the single time period, the 1st pressure detecting point is to pth pressure The peak-to-peak value of monitoring point pressure data, meansigma methods and variance yields；

M-pressure model when () sets up e, duplicon step (d) n time, in calculating one day in the 1st time period Within the n-th time period the 1st～the peak-to-peak value of p pressure monitoring point pressure data, meansigma methods and variance yields, first 1st pressure monitoring point pressure data peak-to-peak value, meansigma methods and variance yields in first the 1st time period of record, and With the corresponding relation of pressure data Yu this pressure data acquisition time, with the time as transverse axis, in the 1st time period 1st pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up model P₁₁；Record the 1st time period Interior 2nd pressure monitoring point pressure data peak-to-peak value, meansigma methods and variance yields, and with pressure data and this pressure The corresponding relation of data acquisition time, with the time as transverse axis, the 2nd pressure monitoring point number pressure in this time period Set up curve according to for the longitudinal axis, i.e. set up model P₁₂；Pth pressure monitoring point pressure in the rest may be inferred this time period Data peak-to-peak value, meansigma methods and variance yields, and with the corresponding relation of pressure data Yu this pressure data acquisition time, With the time as transverse axis, in this time period, pth pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up Model P_1p, in like manner, respectively in the 2nd time period of record the 1st～p pressure monitoring point pressure data peak-to-peak value, Meansigma methods and variance yields, with the corresponding relation of pressure data in the 2nd time period Yu this pressure data acquisition time, With the time as transverse axis, in this time period, pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up model P₂₁～P_2p, the rest may be inferred record respectively in the n-th time period the 1st～p pressure monitoring point pressure data peak-to-peak value, Meansigma methods and variance yields, with the corresponding relation of pressure data in the n-th time period Yu this pressure data acquisition time, With the time as transverse axis, in this time period, pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up model P_n1～P_np.Change dynamic corrections above-mentioned model P according to data₁₁～P_1p、P₂₁～P_2pUntil P_n1～P_np；

F () sets up flow rate pressure model, in recording one day, DMA subregion tap water main line data on flows and p are individual Pressure monitoring point data, first, with different DMA subregion tap water main line datas on flows and the 1st pressure The corresponding relation of monitoring point pressure data, flow is transverse axis, and pressure is that the longitudinal axis sets up the 1st pressure monitoring point stream Amount-pressure model A₁, then, with different DMA subregion tap water main line datas on flows and the 2nd pressure prison The corresponding relation of measuring point pressure data, flow is transverse axis, pressure be the longitudinal axis set up the 2nd pressure monitoring point flow- Pressure model A₂, the rest may be inferred supervises with pth pressure with different DMA subregion tap water main line datas on flows The corresponding relation of measuring point pressure data, flow is transverse axis, pressure be the longitudinal axis set up pth pressure monitoring point flow- Pressure model A_p；

Whether step 2, leak diagnostics unit judges exist leakage point and leakage orientation, according to practical situation, if Widow time length calculated by devise a stratagem, and widow time length is designated as t, and system of the present invention can set the threshold of each item data Value, specifically includes following sub-step:

A () sets current slot as the d time period, counted by formula in step 1 sub-step (a) (1) Calculate the peak-to-peak value of DMA subregion tap water main line data on flows in current the d time period, by step 1 DMA subregion tap water main line flow in formula (2) calculates current the d time period in sub-step (a) The meansigma methods of data, calculates DMA in current the d time period by formula in step 1 sub-step (a) (3) The variance yields of subregion tap water main line data on flows, record peak-to-peak value in the above current the d time period, Meansigma methods and variance yields, with the corresponding relation of data on flows Yu this data acquisition time, with the time as transverse axis, when In front the d time period, data on flows is that the longitudinal axis sets up curve, i.e. sets up model S, by peak-to-peak value in model S, Meansigma methods and variance yields and the time m-discharge model Q of foundation in step 1 sub-step (b)₁～Q_nIn corresponding time Between the model Q of section_dCompared with middle peak-to-peak value, meansigma methods are corresponding with variance yields, if the difference of peak-to-peak value is not less than being System threshold value, the difference of meansigma methods and the difference of variance yields all exceed system thresholds, then judge that this DMA subregion is deposited In leakage, if the difference of peak-to-peak value, meansigma methods and variance yields all exceedes system thresholds, then within this time period with The length of window t calculated flow rate statistical average of defaultVariance yields s_t ²If, this time period initial time For T₁, the end time is T₂, this time period is divided into the 1st window T₁～T₁+ t, the 2nd window t～T₁ + 2t ..., x-th window T₁+ xt～T₂, calculated flow rate statistical average in y-th windowSide Difference s_t ², meansigma methodsCalculated by formula (7),

${\stackrel{\&OverBar;}{X}}_t=\frac{1}{e}\underset{f=1}{\overset{e}{\&Sigma;}}{X}_f---\left(7\right)$

In formula, e represents the total number of data on flows in y-th window, X_fRepresent data on flows in y-th window The f data in total number, variance yields s_t ²Calculated by formula (8),

${s_t}^2=\frac{1}{e-1}\underset{f=1}{\overset{e}{\&Sigma;}}{(X_f-{\stackrel{\&OverBar;}{X}}_t)}^2---\left(8\right)$

Find the 1st meansigma methods of data on flows, variance yields discharge model Q m-with time corresponding in this time period_d Meansigma methods, variance yields compare the window more all exceeding system thresholds, record initial time t of this window₁；Look for The meansigma methods of last 1 data on flows, variance yields discharge model Q m-with time corresponding within this time period_dFlat Average, variance yields compare the window more all exceeding system thresholds, record initial time t of this window₂, the 1st Occur to last, abnormal window occurs that the time difference between abnormal window is designated as Δ t, Δ t by formula (9) Calculate,

Δ t=t₂-t₁ (9)

If Δ t exceedes the maximum time interval of default, then judge to there is leakage；

If b in judging this DMA subregion in () step 2 sub-step (a) there is leakage, then according to step in pipe network The peak-to-peak value of p pressure monitoring point, root in 1 sub-step (c), formula (4) calculates current the d time period The flat of p pressure monitoring point in current the d time period is calculated according to formula in step 1 sub-step (c) (5) Average and calculate p pressure prison in current the d time period according to formula in step 1 sub-step (c) (6) The variance yields of measuring point, if the peak-to-peak value of u pressure monitoring point, meansigma methods and variance yields one of which or two Or three exceed system correspondence threshold value, then find this pressure monitoring point in current the d time period maximum and Minima, according to the acquisition time that the maximum of this pressure monitoring point in current the d time period is corresponding, in step The model S that rapid 2 sub-steps (a) are set up finds the flow value B of correspondence_max, time simultaneously according to current the d Between the maximum of this pressure monitoring point in section, the model A set up in step 1 sub-step (f)_uIn find work as The flow value C that in front the d time period, the maximum of this pressure monitoring point is corresponding_max；During according to current the d Between the minima of this pressure monitoring point is corresponding in section time point, in the model S that step 2 sub-step (a) is set up In find correspondence flow value B_min, simultaneously according to the minima of this pressure monitoring point in current the d time period, The model A set up in step 1 sub-step (f)_uIn find this pressure monitoring point in current the d time period Flow value C corresponding to minima_min, by B_maxWith C_maxCompare, B_minWith C_minCompare, if more than described Two all exceed system thresholds, then judge that this pressure monitoring point place pipeline section exists leakage, complete leakage point Orientation judges；

Step 3, according in step 2, the orientation of leakage point is judged, leak point positioning unit starting be installed on should The sonic transducer of orientation relevant position completes sonic data collection and calculates, according to located in connection survey calculation method Calculate leakage point away from the distance closing on sonic transducer.

The medicine have the advantages that a kind of DMA subregion pipeline network leak on-line checking alignment system, including DMA Subregion tap water main line, DMA subregion the 1st, 2 ... N-1, N tap water bye-pass, data acquisition unit, Pressure sensing cell, sonic detection unit, system server and work station, described data acquisition unit, including Pressure transducer, flow transducer and data acquisition RTU module, wherein pressure transducer, flow transducer peace Being contained on the tap water main line of DMA subregion porch, data acquisition RTU module is arranged on the well of valve well On wall, described pressure transducer, flow transducer connect with two RS-485 in data acquisition RTU module respectively Mouth is connected, for the pressure on the tap water main line collecting DMA subregion porch, data on flows being led to Cross the GPRS/3G/4G module being built in data acquisition RTU module by timing or real-time in the way of data are uploaded To system server；Described DMA subregion the 1st, 2 ... on N-1, N tap water bye-pass, according to field working conditions It is separately installed with pressure sensing cell or sonic detection unit or pressure sensing cell and sonic detection unit, described Pressure sensing cell, including the pressure transducer being arranged on DMA subregion tap water bye-pass and be arranged on neighbour Data acquisition RTU module on the borehole wall of nearly valve well, described sonic detection unit, including being arranged on DMA Pipeline sonic transducer on subregion tap water bye-pass and be arranged on the data acquisition on the borehole wall of adjacent valve well RTU module, described pressure transducer, pipeline sonic transducer respectively with RS-485 in data acquisition RTU module Interface is connected, and pressure and sonic data on the tap water bye-pass that will collect in DMA subregion pass through Be built in the GPRS/3G/4G module of data acquisition RTU module by timing or real-time in the way of data are uploaded to System server, carries out communication by EPA between system server and work station；With prior art phase Ratio, the present invention be suitable for groundwater supply pipe network, be easily installed, with low cost, solve each DMA in city well The end pipe network leak diagnostics of subregion and orientation problem, find leak point in time, processed in time, decrease A large amount of losses of water resource.

Accompanying drawing explanation

Fig. 1 is the population structure block diagram of present system.

Fig. 2 is the work station internal structure block diagram in present system.

Fig. 3 is mounted in the data acquisition unit structured flowchart on DMA subregion tap water main line.

Fig. 4 is mounted in the pressure sensing cell structured flowchart on DMA subregion pipe network bye-pass.

Fig. 5 is mounted in the sonic detection cellular construction block diagram on DMA subregion pipe network bye-pass.

Fig. 6 is mounted in the pressure sensing cell on DMA subregion pipe network bye-pass and sonic detection cellular construction Block diagram.

Fig. 7 is the inventive method flow chart of steps.

Detailed description of the invention

The invention will be further described below in conjunction with the accompanying drawings.

As shown in Fig. 1,2,3,4,5,6, a kind of DMA subregion pipeline network leak on-line checking alignment system, Including DMA subregion tap water main line, DMA subregion the 1st, 2 ... N-1, N tap water bye-pass, data Collecting unit, pressure sensing cell, sonic detection unit, system server and work station, described data acquisition Unit, including pressure transducer, flow transducer and data acquisition RTU module, wherein pressure transducer, stream Quantity sensor is arranged on the tap water main line of DMA subregion porch, and data acquisition RTU module is arranged on On the borehole wall of adjacent valve well, described pressure transducer, flow transducer respectively with in data acquisition RTU module Two RS-485 interfaces are connected, for by the pressure on the tap water main line collecting DMA subregion porch, Data on flows by be built in the GPRS/3G/4G module of data acquisition RTU module with timing or real-time by the way of Data are uploaded to system server；Described DMA subregion the 1st, 2 ... on N-1, N tap water bye-pass, root It is separately installed with pressure sensing cell or sonic detection unit or pressure sensing cell and sonic detection according to field working conditions Unit, described pressure sensing cell, including the pressure transducer being arranged on DMA subregion tap water bye-pass And the data acquisition RTU module being arranged on the borehole wall of adjacent valve well, described sonic detection unit, including peace It is contained in the pipeline sonic transducer on DMA subregion tap water bye-pass and is arranged on the borehole wall of adjacent valve well Data acquisition RTU module, described pressure transducer, pipeline sonic transducer respectively with data acquisition RTU module Upper RS-485 interface is connected, the pressure on the tap water bye-pass that will collect in DMA subregion and sound wave Data by be built in the GPRS/3G/4G module of data acquisition RTU module with timing or real-time by the way of by number According to being uploaded to system server, between system server and work station, carry out communication by EPA；Described Work station, including data collection control unit, statistical model parameter calculation unit, pipe network diagnosis unit, sound spy Property computational analysis unit, leakage point leak hunting positioning unit and DMA partition monitor display unit, wherein, described Data collection control unit, also includes gathering target configuration subelement, data acquisition scheme configuration subelement, number Subelement, real-time database data management subelement, history library interface subelement and phase is resolved according to transmitting-receiving and communications protocol Close position data collecting Collaborative Control subelement, based on data acquisition unit, pressure sensing cell and sonic detection The data that unit gathers, jointly completing pipeline network leak through statistical model parameter calculation unit and pipe network diagnosis unit is The judgement of no existence and the judgement in leakage orientation, sound characteristics computational analysis unit completes to be judged to leak around orientation Pipeline sonic data calculate.The detailed process of system work is: pipe network diagnosis unit and leakage point leak hunting location Unit is by collection target configuration subelement, the data acquisition scheme in DMA partition data acquisition controlling unit Configuration subelement completion system initial configuration, then, data acquisition unit, pressure sensing cell, sound wave are examined Survey the related data that collects of unit and be uploaded to system server.According to the data gathered, statistical model parameter Computing unit calculates water supply statistical model, and pipe network diagnosis unit diagnostic tube Running State, sonic detection unit divides Analysis pipe network acoustical signal characteristic, completes pipe network operation state and the analysis of gathered acoustical signal.Then, then by letting out The leak source positioning unit that leaks hunting is assigned measurement of correlation order and calculates leakage point position, it is achieved the detection to pipeline network leak With location, and by each for pipe network item data and to pipeline network leak detection with location result be shown in DMA subregion On monitoring display interface.

The detection and location method of described a kind of DMA subregion pipeline network leak on-line checking alignment system, including following Step:

Step 1, set up DMA water rationing pipe network operation state rule statistical models, described statistical models Setting up premise is that pipeline is properly functioning and No leakage, according to actual condition, is divided into n time period by 24 hours, Have 1 flow monitoring point, p pressure monitoring point in DMA subregion, specifically include following sub-step:

A in () single time period, in DMA subregion entry data collecting unit, flow transducer gathers m DMA Subregion tap water main line data on flows, gathers 1 data on flows every time, and each data on flows all includes this stream The acquisition time of amount data, finds the maximum max of data on flows in this time period₁And minima min₁, peak-to-peak Value P₁It is calculated by formula (1),

P₁=max₁-min₁ (1)

The meansigma methods of DMA subregion tap water main line data on flows in this time periodCalculated by formula (2) Obtain,

${\stackrel{\&OverBar;}{X}}_1=\frac{1}{m}\underset{i=1}{\overset{m}{\&Sigma;}}{X}_i---\left(2\right)$

In formula, the DMA subregion tap water total number of main line data on flows that m gathers in representing this time period, X_i Represent the i-th data in m DMA subregion tap water main line data on flows, single time in this time period The variance yields s of DMA subregion tap water main line data on flows in section₁ ²It is calculated by formula (3),

${s_1}^2=\frac{1}{m-1}\underset{i=1}{\overset{m}{\&Sigma;}}{(X_i-{\stackrel{\&OverBar;}{X}}_1)}^2---\left(3\right)$

M-discharge model when () sets up b, duplicon step (a) n time, in calculating respectively one day during n difference Between DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods and variance yields, first record the 1st in section DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods and variance yields in the individual time period, and with stream Amount data and the corresponding relation of this data acquisition time, with the time as transverse axis, in this time period, DMA subregion enters The data on flows of mouth data acquisition unit flow transducer is that the longitudinal axis sets up curve, i.e. sets up model Q₁, then with DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods and variance yields in 2nd time period, and With the corresponding relation of data on flows Yu this data acquisition time, with the time as transverse axis, in this time period, DMA divides The data on flows of district's entry data collecting unit flow transducer is that the longitudinal axis sets up curve, i.e. sets up model Q₂, depend on This analogizes DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods and side in the n-th time period of record Difference, and with the corresponding relation of data on flows Yu this data acquisition time, with the time as transverse axis, in this time period The data on flows of DMA subregion entry data collecting unit flow transducer is that the longitudinal axis sets up curve, i.e. sets up model Q_n, according to the change dynamic corrections above-mentioned model Q of data₁～Q_n；

C in () single time period, in pressure sensing cell, pressure transducer gathers k pressure at single pressure monitoring point Force data, gathers 1 pressure data every time, and each pressure data all includes the acquisition time of this pressure data, So within the single time period, single monitoring point gathers pressure data k altogether, finds number pressure in this time period According to maximum max₂And minima min₂, peak-to-peak value P₂Obtained by formula (4),

P₂=max₂-min₂ (4)

The meansigma methods of single pressure monitoring point pressure dataIt is calculated by formula (5),

${\stackrel{\&OverBar;}{X}}_2=\frac{1}{k}\underset{j=1}{\overset{k}{\&Sigma;}}{X}_j---\left(5\right)$

In formula, the k total number of pressure data that in representing this time period, single pressure monitoring point gathers, X_jWhen representing this Between in section in jth data, single pressure monitoring point number pressure in the pressure data that gathers of single pressure monitoring point According to variance yields s₂ ²It is calculated by formula (6),

${s_2}^2=\frac{1}{k-1}\underset{j=1}{\overset{k}{\&Sigma;}}{(X_j-{\stackrel{\&OverBar;}{X}}_2)}^2---\left(6\right)$

D () duplicon step (c) p time, in calculating the single time period, the 1st pressure detecting point is to pth pressure The peak-to-peak value of monitoring point pressure data, meansigma methods and variance yields；

M-pressure model when () sets up e, duplicon step (d) n time, in calculating one day in the 1st time period Within the n-th time period the 1st～the peak-to-peak value of p pressure monitoring point pressure data, meansigma methods and variance yields, first 1st pressure monitoring point pressure data peak-to-peak value, meansigma methods and variance yields in first the 1st time period of record, and With the corresponding relation of pressure data Yu this pressure data acquisition time, with the time as transverse axis, in the 1st time period 1st pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up model P₁₁；Record the 1st time period Interior 2nd pressure monitoring point pressure data peak-to-peak value, meansigma methods and variance yields, and with pressure data and this pressure The corresponding relation of data acquisition time, with the time as transverse axis, the 2nd pressure monitoring point number pressure in this time period Set up curve according to for the longitudinal axis, i.e. set up model P₁₂；Pth pressure monitoring point pressure in the rest may be inferred this time period Data peak-to-peak value, meansigma methods and variance yields, and with the corresponding relation of pressure data Yu this pressure data acquisition time, With the time as transverse axis, in this time period, pth pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up Model P_1p, in like manner, respectively in the 2nd time period of record the 1st～p pressure monitoring point pressure data peak-to-peak value, Meansigma methods and variance yields, with the corresponding relation of pressure data in the 2nd time period Yu this pressure data acquisition time, With the time as transverse axis, in this time period, pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up model P₂₁～P_2p, the rest may be inferred record respectively in the n-th time period the 1st～p pressure monitoring point pressure data peak-to-peak value, Meansigma methods and variance yields, with the corresponding relation of pressure data in the n-th time period Yu this pressure data acquisition time, With the time as transverse axis, in this time period, pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up model P_n1～P_np.Change dynamic corrections above-mentioned model P according to data₁₁～P_1p、P₂₁～P_2pUntil P_n1～P_np；

F () sets up flow rate pressure model, in recording one day, DMA subregion tap water main line data on flows and p are individual Pressure monitoring point data, first, with different DMA subregion tap water main line datas on flows and the 1st pressure The corresponding relation of monitoring point pressure data, flow is transverse axis, and pressure is that the longitudinal axis sets up the 1st pressure monitoring point stream Amount-pressure model A₁, then, with different DMA subregion tap water main line datas on flows and the 2nd pressure prison The corresponding relation of measuring point pressure data, flow is transverse axis, pressure be the longitudinal axis set up the 2nd pressure monitoring point flow- Pressure model A₂, the rest may be inferred supervises with pth pressure with different DMA subregion tap water main line datas on flows The corresponding relation of measuring point pressure data, flow is transverse axis, pressure be the longitudinal axis set up pth pressure monitoring point flow- Pressure model A_p；

Whether step 2, leak diagnostics unit judges exist leakage point and leakage orientation, according to practical situation, if Widow time length calculated by devise a stratagem, and widow time length is designated as t, and system of the present invention can set the threshold of each item data Value, specifically includes following sub-step:

A () sets current slot as the d time period, counted by formula in step 1 sub-step (a) (1) Calculate the peak-to-peak value of DMA subregion tap water main line data on flows in current the d time period, by step 1 DMA subregion tap water main line flow in formula (2) calculates current the d time period in sub-step (a) The meansigma methods of data, calculates DMA in current the d time period by formula in step 1 sub-step (a) (3) The variance yields of subregion tap water main line data on flows, record peak-to-peak value in the above current the d time period, Meansigma methods and variance yields, with the corresponding relation of data on flows Yu this data acquisition time, with the time as transverse axis, when In front the d time period, data on flows is that the longitudinal axis sets up curve, i.e. sets up model S, by peak-to-peak value in model S, Meansigma methods and variance yields and the time m-discharge model Q of foundation in step 1 sub-step (b)₁～Q_nIn corresponding time Between the model Q of section_dCompared with middle peak-to-peak value, meansigma methods are corresponding with variance yields, if the difference of peak-to-peak value is not less than being System threshold value, the difference of meansigma methods and the difference of variance yields all exceed system thresholds, then judge that this DMA subregion is deposited In leakage, if the difference of peak-to-peak value, meansigma methods and variance yields all exceedes system thresholds, then within this time period with The length of window t calculated flow rate statistical average of defaultVariance yields s_t ²If, this time period initial time For T₁, the end time is T₂, this time period is divided into the 1st window T₁～T₁+ t, the 2nd window t～T₁ + 2t ..., x-th window T₁+ xt～T₂, calculated flow rate statistical average in y-th windowSide Difference s_t ², meansigma methodsCalculated by formula (7),

${\stackrel{\&OverBar;}{X}}_t=\frac{1}{e}\underset{f=1}{\overset{e}{\&Sigma;}}{X}_f---\left(7\right)$

In formula, e represents the total number of data on flows in y-th window, X_fRepresent data on flows in y-th window The f data in total number, variance yields s_t ²Calculated by formula (8),

${s_t}^2=\frac{1}{e-1}\underset{f=1}{\overset{e}{\&Sigma;}}{(X_f-{\stackrel{\&OverBar;}{X}}_t)}^2---\left(8\right)$

Find the 1st meansigma methods of data on flows, variance yields discharge model Q m-with time corresponding in this time period_d Meansigma methods, variance yields compare the window more all exceeding system thresholds, record initial time t of this window₁；Look for The meansigma methods of last 1 data on flows, variance yields discharge model Q m-with time corresponding within this time period_dFlat Average, variance yields compare the window more all exceeding system thresholds, record initial time t of this window₂, the 1st Occur to last, abnormal window occurs that the time difference between abnormal window is designated as Δ t, Δ t by formula (9) Calculate,

Δ t=t₂-t₁ (9)

If Δ t exceedes the maximum time interval of default, then judge to there is leakage；

If b in judging this DMA subregion in () step 2 sub-step (a) there is leakage, then according to step in pipe network The peak-to-peak value of p pressure monitoring point, root in 1 sub-step (c), formula (4) calculates current the d time period The flat of p pressure monitoring point in current the d time period is calculated according to formula in step 1 sub-step (c) (5) Average and calculate p pressure prison in current the d time period according to formula in step 1 sub-step (c) (6) The variance yields of measuring point, if the peak-to-peak value of u pressure monitoring point, meansigma methods and variance yields one of which or two Or three exceed system correspondence threshold value, then find this pressure monitoring point in current the d time period maximum and Minima, according to the acquisition time that the maximum of this pressure monitoring point in current the d time period is corresponding, in step The model S that rapid 2 sub-steps (a) are set up finds the flow value B of correspondence_max, time simultaneously according to current the d Between the maximum of this pressure monitoring point in section, the model A set up in step 1 sub-step (f)_uIn find work as The flow value C that in front the d time period, the maximum of this pressure monitoring point is corresponding_max；During according to current the d Between the minima of this pressure monitoring point is corresponding in section time point, in the model S that step 2 sub-step (a) is set up In find correspondence flow value B_min, simultaneously according to the minima of this pressure monitoring point in current the d time period, The model A set up in step 1 sub-step (f)_uIn find this pressure monitoring point in current the d time period Flow value C corresponding to minima_min, by B_maxWith C_maxCompare, B_minWith C_minCompare, if more than described Two all exceed system thresholds, then judge that this pressure monitoring point place pipeline section exists leakage, complete leakage point Orientation judges；

Step 3, according in step 2, the orientation of leakage point is judged, leak point positioning unit starting be installed on The sonic transducer of this orientation relevant position completes sonic data collection and calculates, according to located in connection survey calculation side Method calculates leakage point away from the distance closing on sonic transducer.

Claims (2)

1. a DMA subregion pipeline network leak on-line checking alignment system, including DMA subregion tap water Main line, DMA subregion the 1st, 2 ... N-1, N tap water bye-pass, data acquisition unit, pressure are examined Survey unit, sonic detection unit, system server and work station, it is characterised in that: described data acquisition list Unit, including pressure transducer, flow transducer and data acquisition RTU module, wherein pressure transducer, Flow transducer is arranged on the tap water main line of DMA subregion porch, and data acquisition RTU module is pacified Be contained on the borehole wall of adjacent valve well, described pressure transducer, flow transducer respectively with data acquisition RTU In module, two RS-485 interfaces are connected, for being responsible for by the tap water collecting DMA subregion porch Pressure on road, data on flows by be built in the GPRS/3G/4G module of data acquisition RTU module with Data are uploaded to system server by timing or real-time mode；Described DMA subregion the 1st, 2 ... N-1, On N tap water bye-pass, according to field working conditions be separately installed with pressure sensing cell or sonic detection unit or Pressure sensing cell and sonic detection unit, described pressure sensing cell, including being arranged on DMA subregion certainly Pressure transducer on water bye-pass and the data acquisition RTU mould being arranged on the borehole wall of adjacent valve well Block, described sonic detection unit, including the pipeline sound sensing being arranged on DMA subregion tap water bye-pass Device and the data acquisition RTU module being arranged on the borehole wall of adjacent valve well, described pressure transducer, pipe Road sonic transducer is connected with RS-485 interface in data acquisition RTU module respectively, for collecting DMA The pressure on tap water bye-pass in subregion and sonic data are by being built in data acquisition RTU module GPRS/3G/4G module by timing or real-time in the way of data are uploaded to system server, system server And carry out communication by EPA between work station；Described work station, including data collection control unit, Statistical model parameter calculation unit, pipe network diagnosis unit, sound characteristics computational analysis unit, leakage point leak hunting fixed Bit location and DMA partition monitor display unit, wherein, described data collection control unit, also include adopting It is single that collection target configuration subelement, data acquisition scheme configuration subelement, data transmit-receive and communications protocol resolve son Unit, real-time database data management subelement, history library interface subelement and located in connection data acquisition Collaborative Control Subelement, the data gathered based on data acquisition unit, pressure sensing cell and sonic detection unit, through system Meter model parameter calculation unit and pipe network diagnosis unit jointly complete judgement that whether pipeline network leak exist and let out The judgement in leakage orientation, sound characteristics computational analysis unit completes to be judged to leak the pipeline sonic data around orientation Calculate.

A kind of inspection of DMA subregion pipeline network leak on-line checking alignment system Measure method for position, it is characterised in that comprise the following steps:

Step 1, set up DMA water rationing pipe network operation state rule statistical models, described statistics mould Premise set up by type is that pipeline is properly functioning and No leakage, according to actual condition, is divided into n time by 24 hours Section, has 1 flow monitoring point, p pressure monitoring point, specifically includes following sub-step in DMA subregion Rapid:

A in () single time period, in DMA subregion entry data collecting unit, flow transducer gathers m time DMA subregion tap water main line data on flows, gathers 1 data on flows every time, and each data on flows is all wrapped Containing the acquisition time of this data on flows, find the maximum max of data on flows in this time period₁And minima min₁, peak-to-peak value P₁It is calculated by formula (1),

P₁=max₁-min₁ (1)

The meansigma methods of DMA subregion tap water main line data on flows in this time periodCounted by formula (2) Obtain,

${\stackrel{\&OverBar;}{X}}_1=\frac{1}{m}\underset{i=1}{\overset{m}{\&Sigma;}}{X}_i---\left(2\right)$

In formula, the DMA subregion tap water total number of main line data on flows that m gathers in representing this time period, X_iRepresent the i-th data in m DMA subregion tap water main line data on flows in this time period, single The variance yields s of DMA subregion tap water main line data on flows in the individual time period₁ ²Calculated by formula (3) Obtain,

${s_1}^2=\frac{1}{m-1}\underset{i=1}{\overset{m}{\&Sigma;}}{(X_i-{\stackrel{\&OverBar;}{X}}_1)}^2---\left(3\right)$

M-discharge model when () sets up b, duplicon step (a) n time, n difference in calculating respectively a day In time period, DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods and variance yields, first remember Record DMA subregion tap water main line data on flows peak-to-peak value in the 1st time period, meansigma methods and variance yields, And with the corresponding relation of data on flows Yu this data acquisition time, with the time as transverse axis, DMA in this time period The data on flows of subregion entry data collecting unit flow transducer is that the longitudinal axis sets up curve, i.e. sets up model Q₁, then with DMA subregion tap water main line data on flows peak-to-peak value, meansigma methods in the 2nd time period And variance yields, and with the corresponding relation of data on flows Yu this data acquisition time, with the time as transverse axis, this time Between in section the data on flows of DMA subregion entry data collecting unit flow transducer be that the longitudinal axis sets up curve, I.e. set up model Q₂, the rest may be inferred records DMA subregion tap water main line flow number in the n-th time period According to peak-to-peak value, meansigma methods and variance yields, and with the corresponding relation of data on flows Yu this data acquisition time, with Time is transverse axis, the data on flows of DMA subregion entry data collecting unit flow transducer in this time period Set up curve for the longitudinal axis, i.e. set up model Q_n, according to the change dynamic corrections above-mentioned model Q of data₁～Q_n；

C in () single time period, in pressure sensing cell, pressure transducer gathers k time at single pressure monitoring point Pressure data, gathers 1 pressure data every time, and each pressure data all includes the collection of this pressure data Time, so within the single time period, single monitoring point gathers pressure data k altogether, finds this time period The maximum max of interior pressure data₂And minima min₂, peak-to-peak value P₂Obtained by formula (4),

P₂=max₂-min₂ (4)

The meansigma methods of single pressure monitoring point pressure dataIt is calculated by formula (5),

${\stackrel{\&OverBar;}{X}}_2=\frac{1}{k}\underset{j=1}{\overset{k}{\&Sigma;}}{X}_j---\left(5\right)$

In formula, the k total number of pressure data that in representing this time period, single pressure monitoring point gathers, X_jRepresent Jth data in the pressure data that in this time period, single pressure monitoring point gathers, single pressure monitoring point The variance yields s of pressure data₂ ²It is calculated by formula (6),

${s_2}^2=\frac{1}{k-1}\underset{j=1}{\overset{k}{\&Sigma;}}{(X_j-{\stackrel{\&OverBar;}{X}}_2)}^2---\left(6\right)$

D () duplicon step (c) p time, in calculating the single time period, the 1st pressure detecting point is pressed to pth Peak-to-peak value, meansigma methods and the variance yields of power monitoring point pressure data；

M-pressure model when () sets up e, duplicon step (d) n time, the 1st time in calculating one day To the in the n-th time period the 1st～the peak-to-peak value of p pressure monitoring point pressure data, meansigma methods and variance in section 1st pressure monitoring point pressure data peak-to-peak value, meansigma methods and side in value, first the 1st time period of record Difference, and with the corresponding relation of pressure data Yu this pressure data acquisition time, with the time as transverse axis, the 1st In the individual time period, the 1st pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up model P₁₁；Note Record in the 1st time period the 2nd pressure monitoring point pressure data peak-to-peak value, meansigma methods and variance yields, and with The corresponding relation of pressure data and this pressure data acquisition time, with the time as transverse axis, in this time period the 2nd Individual pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up model P₁₂；The rest may be inferred this time period Interior pth pressure monitoring point pressure data peak-to-peak value, meansigma methods and variance yields, and with pressure data and this pressure The corresponding relation of force data acquisition time, with the time as transverse axis, in this time period, pth pressure monitoring presses Force data is that the longitudinal axis sets up curve, i.e. sets up model P_1p, in like manner, respectively in the 2nd time period of record the 1～p pressure monitoring point pressure data peak-to-peak value, meansigma methods and variance yields, with pressure in the 2nd time period Data and the corresponding relation of this pressure data acquisition time, with the time as transverse axis, pressure monitoring in this time period Point pressure data are that the longitudinal axis sets up curve, i.e. set up model P₂₁～P_2p, the rest may be inferred when recording n-th respectively Between in section the 1st～p pressure monitoring point pressure data peak-to-peak value, meansigma methods and variance yields, with the n-th time Pressure data and the corresponding relation of this pressure data acquisition time in section, with the time as transverse axis, in this time period Pressure monitoring point pressure data is that the longitudinal axis sets up curve, i.e. sets up model P_n1～P_np.Change according to data Dynamic corrections above-mentioned model P₁₁～P_1p、P₂₁～P_2pUntil P_n1～P_np；

F () sets up flow rate pressure model, in recording one day DMA subregion tap water main line data on flows and P pressure monitoring point data, first, with different DMA subregion tap water main line datas on flows and the 1st The corresponding relation of individual pressure monitoring point pressure data, flow is transverse axis, and pressure is that the longitudinal axis sets up the 1st pressure Monitoring point flow rate pressure model A₁, then, with different DMA subregion tap water main line datas on flows with The corresponding relation of the 2nd pressure monitoring point pressure data, flow is transverse axis, and pressure is that the longitudinal axis sets up the 2nd Pressure monitoring point flow rate pressure model A₂, the rest may be inferred with different DMA subregion tap water main line flows Data and the corresponding relation of pth pressure monitoring point pressure data, flow is transverse axis, and pressure is that the longitudinal axis is set up Pth pressure monitoring point flow rate pressure model A_p；

Whether step 2, leak diagnostics unit judges exist leakage point and leakage orientation, according to practical situation, Setup algorithm widow time length, widow time length is designated as t, and system of the present invention can set each item number According to threshold value, specifically include following sub-step:

A () sets current slot as the d time period, by formula in step 1 sub-step (a) (1) Calculate the peak-to-peak value of DMA subregion tap water main line data on flows in current the d time period, by step DMA subregion tap water supervisor in formula (2) calculates current the d time period in rapid 1 sub-step (a) The meansigma methods of road data on flows, when calculating current the d by formula in step 1 sub-step (a) (3) Between the variance yields of DMA subregion tap water main line data on flows in section, record the above current d Peak-to-peak value, meansigma methods and variance yields in time period, with the corresponding relation of data on flows Yu this data acquisition time, With the time as transverse axis, in current the d time period, data on flows is that the longitudinal axis sets up curve, i.e. sets up model S, By peak-to-peak value, meansigma methods and variance yields and the time m-flow of foundation in step 1 sub-step (b) in model S Model Q₁～Q_nIn the model Q of corresponding time period_dCompared with middle peak-to-peak value, meansigma methods are corresponding with variance yields, If the difference of peak-to-peak value all exceedes system threshold not less than system thresholds, the difference of meansigma methods and the difference of variance yields Value, then judge that this DMA subregion exists leakage, if the difference of peak-to-peak value, meansigma methods and variance yields all exceedes System thresholds, then with the length of window t calculated flow rate statistical average of default within this time period Variance yields s_t ²If this time period initial time is T₁, the end time is T₂, this time period is divided into the 1st Individual window T₁～T₁+ t, the 2nd window t～T₁+ 2t ..., x-th window T₁+ xt～T₂, at y Calculated flow rate statistical average in individual windowVariance yields s_t ², meansigma methodsCalculated by formula (7),

${\stackrel{\&OverBar;}{X}}_t=\frac{1}{e}\underset{f=1}{\overset{e}{\&Sigma;}}{X}_f---\left(7\right)$

In formula, e represents the total number of data on flows in y-th window, X_fRepresent flow number in y-th window According to the f data in total number, variance yields s_t ²Calculated by formula (8),

${s_t}^2=\frac{1}{e-1}\underset{f=1}{\overset{e}{\&Sigma;}}{(X_f-{\stackrel{\&OverBar;}{X}}_t)}^2---\left(8\right)$

Find the 1st meansigma methods of data on flows, variance yields discharge model m-with time corresponding in this time period Q_dMeansigma methods, variance yields compare the window more all exceeding system thresholds, record initial time t of this window₁； The meansigma methods of last 1 data on flows, variance yields discharge model Q m-with time corresponding in finding this time period_d Meansigma methods, variance yields compare the window more all exceeding system thresholds, record initial time t of this window₂, 1st occurs to last, abnormal window occurs that the time difference between abnormal window is designated as Δ t, Δ t and leads to Cross formula (9) to calculate,

Δ t=t₂-t₁ (9)

If Δ t exceedes the maximum time interval of default, then judge to there is leakage；

If b in judging this DMA subregion in () step 2 sub-step (a) there is leakage, then according to step in pipe network The peak-to-peak of p pressure monitoring point in formula (4) calculates current the d time period in rapid 1 sub-step (c) Value, calculate p pressure prison in current the d time period according to formula in step 1 sub-step (c) (5) The meansigma methods of measuring point and calculating in current the d time period according to formula in step 1 sub-step (c) (6) The variance yields of p pressure monitoring point, if the peak-to-peak value of u pressure monitoring point, meansigma methods and variance yields its In one or two or three exceed system correspondence threshold value, then find this pressure prison in current the d time period The maximum of measuring point and minima, corresponding according to the maximum of this pressure monitoring point in current the d time period Acquisition time, find in the model S that step 2 sub-step (a) is set up correspondence flow value B_max, Simultaneously according to the maximum of this pressure monitoring point in current the d time period, in step 1 sub-step (f) The model A of middle foundation_uIn find the stream that the maximum of this pressure monitoring point is corresponding in current the d time period Value C_max；According to the time point that the minima of this pressure monitoring point in current the d time period is corresponding, The model S that step 2 sub-step (a) is set up finds the flow value B of correspondence_min, simultaneously according to current d The minima of this pressure monitoring point in the individual time period, the model A set up in step 1 sub-step (f)_uIn Find the flow value C that the minima of this pressure monitoring point interior of current the d time period is corresponding_min, by B_max With C_maxCompare, B_minWith C_minCompare, if described above two all exceed system thresholds, then judge this pressure There is leakage in place, power monitoring point pipeline section, completes the orientation to leakage point and judge；

Step 3, according in step 2, the orientation of leakage point is judged, leak point positioning unit starting be installed on The sonic transducer of this orientation relevant position completes sonic data collection and calculates, according to located in connection survey calculation Method calculates leakage point away from the distance closing on sonic transducer.