CN110864227B - Water supply pipe network state monitoring system and method - Google Patents

Water supply pipe network state monitoring system and method Download PDF

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CN110864227B
CN110864227B CN201911058067.XA CN201911058067A CN110864227B CN 110864227 B CN110864227 B CN 110864227B CN 201911058067 A CN201911058067 A CN 201911058067A CN 110864227 B CN110864227 B CN 110864227B
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monitoring
pipe network
pipeline
water supply
signal
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CN110864227A (en
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刘书明
于喜鹏
吴雪
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Tsinghua University
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
    • F17D—PIPE-LINE SYSTEMS; PIPE-LINES
    • F17D5/00—Protection or supervision of installations
    • F17D5/02—Preventing, monitoring, or locating loss
    • F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass

Abstract

The invention relates to a water supply network state monitoring system and a method, which are characterized in that the monitoring system comprises wireless monitoring equipment, a data processing cloud end and a control end; the wireless monitoring devices are arranged on nodes of the pipe network pipeline at intervals, each wireless monitoring device comprises a monitoring device, a communication device, a power supply device and a controller, and the monitoring devices are used for monitoring water quality, pressure and/or flow signals at the corresponding nodes of the pipe network pipeline, transmitting acoustic signals into the pipe network pipeline and monitoring acoustic signals at the corresponding nodes of the pipe network pipeline; the data processing cloud end is used for determining the pipe network state of each node of the water supply pipe network; the control end is used for obtaining the monitoring instruction of each monitoring device according to the state of the pipe network, updating the pipe network state of the water supply pipe network, and then sending the pipe network state to the corresponding controller, so that each controller controls the corresponding monitoring device to carry out monitoring operation according to the corresponding monitoring instruction.

Description

Water supply pipe network state monitoring system and method
Technical Field
The invention relates to a water supply network state monitoring system and method, and belongs to the field of water supply systems.
Background
Nowadays, the scale of city water supply pipe network constantly enlarges, and simultaneously, the water supply pipe network of early establishment also faces the ageing problem of not equidimension, leads to the structure of water supply pipe network to change, seriously influences the water supply ability of pipe network. The cost required for replacing an aged water supply pipe network and improving the performance of the pipe network is huge. Therefore, there is a need for an efficient monitoring method for monitoring the operational status and the status of the pipes of the water supply network. Various technical means are developed by various scholars and organizations for diagnosing the state of the pipeline of the pipe network, and the direct methods include electromagnetic-based monitoring methods, pipe pressure-based monitoring methods, imaging-based monitoring methods, tracer gas-based monitoring methods and acoustic-based monitoring methods. These methods are basically capable of detecting the breakage of the water supply network pipe, but are insufficient in the ability to identify the thickness change of the inner and outer walls of the water supply network pipe due to corrosion or the like. The monitoring method based on electromagnetism can only reflect the external damage of the water supply network pipeline or the residual wall thickness of the water supply network, but cannot reflect the corrosion and the blockage of the inner wall of the water supply network pipeline; the monitoring method based on the pressure in the pipe is most typically a method based on transient flow, and although the method can monitor the corrosion and blockage of the inner wall of the pipeline of the water supply network, the valve of the water supply network needs to be opened and closed, so that the water supply is seriously influenced; the monitoring method based on imaging comprises a closed circuit television monitoring method (CCTV), laser scanning and the like, which can well reflect the internal state of the pipeline of the water supply network, but the invasive monitoring is easy to cause the corrosion layer and the biological layer in the pipeline to fall off, so that the water quality problems of turbid water, red water and the like are caused, and meanwhile, the water supply network is required to have a larger pipe diameter and is difficult to apply; the monitoring method based on the tracer gas can only find the damage of the pipeline of the water supply network; the monitoring method based on acoustics mainly comprises a correlator, a sonar, an intelligent Ball (Smart Ball) and the like, wherein the correlator can only find leakage, and the sonar and the intelligent Ball need to enter the water supply network pipeline, so that the monitoring method based on the acoustics faces the same dilemma as the monitoring method based on imaging. The indirect method mainly comprises a satellite method, a thermal imaging method and the like, monitoring is realized by measuring the change of the electromagnetic and thermodynamic properties of surrounding soil caused by drinking water leaked after the water supply network pipeline is damaged, only the damage can be reflected, and the internal state of the water supply network pipeline cannot be monitored. The robot method mainly adopts the robot to enter the water supply pipeline to check the state of the pipeline in the pipeline network, and the robot can be combined with an acoustic method, an imaging method and the like and also has the same problems with a monitoring method based on imaging.
The water supply networks in cities of China are large in scale and there is a great demand for on-line monitoring systems, however, there are only a few systems and methods for monitoring water supply networks in cities. The prior art discloses a wireless monitoring system for a city water supply pipe network, which is characterized in that an underground communication model is established based on a low-speed short-distance wireless communication purple peak technology (2.4G Hz ZigBee), and a plurality of sensors such as pressure, flow and hydrophone can be fused to realize monitoring of leakage of the water supply pipe network; the prior art also discloses a water supply network monitoring system, which is based on a narrow-band internet of things communication model, integrates flow and pressure sensors, monitors the operation condition of a pipeline, but can not realize leakage monitoring through the system; other disclosed prior arts collect the pipe flow and pressure data by certain communication means and sensor arrangement methods, and cannot realize monitoring of the internal state of the water supply network.
However, when the corrosion and blockage of the water supply network, which is the other side of the structural problem of the water supply network, are identified, the diameter of the water supply network pipeline is required to be large enough, the water supply is seriously influenced by opening and closing a valve and monitoring in a complete invasive manner, and the problems can not well monitor the state of the pipe network in the prior art.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a water supply network status monitoring system and method capable of monitoring the status of a water supply network.
In order to achieve the purpose, the invention adopts the following technical scheme: a water supply network state monitoring system is characterized by comprising wireless monitoring equipment, a data processing cloud end and a control end; the wireless monitoring devices are arranged on nodes of a pipe network pipeline at intervals, each wireless monitoring device comprises a monitoring device, a communication device, a power supply device and a controller, the monitoring devices are used for monitoring water quality, pressure and/or flow signals at the nodes corresponding to the pipe network pipeline in real time, transmitting acoustic signals to the pipe network pipeline and monitoring acoustic signals at the nodes corresponding to the pipe network pipeline, sending the monitored signals to the data processing cloud end through the corresponding communication devices, the controller is used for controlling the monitoring devices and the communication devices to be turned on or off, and the power supply device is used for supplying power to all power utilization parts corresponding to the wireless monitoring devices; the data processing cloud end is used for determining the pipe network state of each node of the water supply pipe network according to the signals monitored by each monitoring device in real time and a preset pipe network state range; the control end is used for obtaining a monitoring instruction of each monitoring device according to the determined pipe network state of each node of the water supply network, updating the pipe network state of the water supply network, and sending the monitoring instruction to the corresponding controller through the data processing cloud end through the corresponding communication device, so that each controller controls the corresponding monitoring device to perform monitoring operation according to the corresponding monitoring instruction.
Furthermore, each monitoring device comprises a hydrophone, a water quality sensor, a pressure sensor and/or a flow sensor; the hydrophone is used for transmitting acoustic signals into the pipe network pipeline and monitoring the acoustic signals in the pipe network pipeline; the water quality sensor is used for monitoring a water quality signal at a corresponding node of a pipe network pipeline; the pressure sensor is used for monitoring pressure signals at corresponding nodes of the pipeline of the pipe network; the flow sensor is used for monitoring flow signals at corresponding nodes of the pipeline of the pipe network.
Further, each of the power supply devices includes a power generation unit and a battery unit; the pipe network pipeline is provided with a plurality of screw holes corresponding to the positions of the nodes, each power generation unit is provided with a turbine, each turbine penetrates through the corresponding screw hole to penetrate into the pipe network pipeline, and the power generation unit is used for converting mechanical energy of water flow in the pipe network pipeline into electric energy through the turbine and supplying power to each power utilization part of the wireless monitoring equipment; the battery unit is connected with the corresponding controller and used for supplying power to each power utilization component of the wireless monitoring equipment when the power generation unit is insufficient in power; in addition, when the power provided by the power generation unit exceeds the power required by the wireless monitoring device, the power generation unit is used for charging the battery unit.
Further, each wireless monitoring device comprises two monitoring states of a silent period and an active period; in a silent period, the wireless monitoring equipment only monitors acoustic signals in the pipe network pipeline, wherein the acoustic signals are passive monitoring acoustic signals; in the active period, the wireless monitoring equipment immediately monitors the acoustic signal in the pipe network pipeline after transmitting the acoustic signal with certain frequency and intensity, and the monitored acoustic signal is an active monitoring acoustic signal.
Further, the pipe network state comprises an operation state, a pipe noise intensity and a pipe network pipeline state, the pipe network state range comprises a water quality range, a flow range, a pressure range and a noise range, and an operation state determination module, a pipe noise intensity determination module and a pipe network pipeline state determination module are arranged in the data processing cloud; the operation state determining module is used for determining the operation state of the water supply network according to the water quality signal, the pressure signal and/or the flow signal monitored by the wireless monitoring equipment and the preset water quality range, the preset pressure range and/or the preset flow range; the in-pipe noise intensity determination module is used for determining the in-pipe noise intensity of the water supply pipe network according to the passive monitoring acoustic signal monitored by the wireless monitoring equipment and a preset noise range; the pipe network pipeline state determining module is used for determining the pipe network pipeline state of the water supply pipe network according to the active monitoring acoustic signal and the passive monitoring acoustic signal monitored by the wireless monitoring equipment.
A method for monitoring the state of a water supply pipe network is characterized by comprising the following steps: 1) when the monitoring period begins, the wireless monitoring equipment enters a silent period, only each monitoring device monitors the acoustic signal existing at the corresponding node, and the monitored acoustic signal is the passive monitoring acoustic signal xs(t); 2) the data processing cloud respectively calculates each passive monitoring acoustic signal xs(t) comparing the calculated power P with a preset noise range, and entering step 3 if the calculated power P is larger than the noise range; if the calculated power P is less than the noise range, step 5) is entered, wherein the acoustic signal x is passively monitoredsThe power P of (t) is:
Figure BDA0002257082650000031
where T denotes the signal period, p0Denotes the density of water, c0Representing the propagation velocity of sound waves in water; judging the noise intensity in the pipe of the water supply pipe network, and entering the step 3) if the noise intensity in the pipe is larger than a preset noise range; if the intensity of the noise in the pipe is not larger than the preset noise range, entering the step 5); 3) data processing cloud port is to each passive monitoring acoustic signal xs(t) performing interpretation calculation to determine whether the pipeline of the pipe network leaks, and if the pipeline of the pipe network does not leak, entering the step 4); if the pipeline of the pipe network leaks, determining the position of the leakage, and entering the step 7); 4) each monitoring device corresponds to the water quality signal, the pressure signal and/or the flow signal at the node and is presetComparing the fixed water quality range, the pressure range and/or the flow range, and if any signal exceeds the corresponding preset range, judging that the running state of the water supply network is abnormal, and entering the step 7); if each signal does not exceed the corresponding preset range, the running state of the water supply network is normal, the pipe network state of the water supply network is updated, and the step 1) is directly carried out; 5) when the wireless monitoring equipment enters an active period, each monitoring device transmits an acoustic signal x with certain frequency and intensityI(t) then, it starts monitoring the reflected acoustic signal xR(t) the adjacent monitoring device immediately starts monitoring the transmitted acoustic signal xT(t) reflected acoustic signal x at this timeR(t) and a transmitted acoustic signal xT(t) is the active monitoring acoustic signal; 6) the data processing cloud end carries out interpretation calculation on each active monitoring sound signal, whether a pipe network pipeline is corroded or blocked is determined, if the pipe network pipeline is not corroded or blocked, the pipe network state of the water supply pipe network is updated, and the step 1 is directly carried out); if the pipeline of the pipe network is corroded or blocked, determining the size and the position of the corrosion or the blockage, and entering a step 7); 7) and (3) the control end obtains the monitoring instruction of each monitoring device according to the determined pipe network state, updates the pipe network state of the water supply pipe network, and sends the monitoring instruction to the corresponding controller through the corresponding communication device through the data processing cloud, so that each controller controls the corresponding monitoring device to perform monitoring operation according to the corresponding monitoring instruction, and then the step 1) is carried out.
Further, the specific process of step 3) is as follows: 3.1) data processing cloud computing passive monitoring of acoustic signals xs(t) kurtosis factor, passive monitoring of acoustic signal x for monitorings(t) performing empirical mode decomposition, calculating the mean square error and information entropy of eigenmode functions of the previous 6 decompositions, and monitoring the passive monitoring acoustic signal xs(t) respectively carrying out Fourier transform to obtain average power density and frequency centroid, obtaining 15 characteristic values in total, and representing passive monitoring acoustic signal x monitored by wireless monitoring equipment i by characteristic vector feature (i) formed by the 15 characteristic valuess(t); 3.2) normalizing each characteristic value to obtain a normalized passive monitoring sound signal feature (i)k：
Figure BDA0002257082650000041
Wherein, feature (i)kExpressing the kth characteristic value of the normalized passive monitoring acoustic signal corresponding to the wireless monitoring equipment i, wherein y expresses an intermediate variable; 3.3) carrying out k-means clustering on the normalized passive monitoring acoustic signals, judging whether an outlier characteristic vector exists, if so, leaking a pipe network pipeline, monitoring a leakage signal by a wireless monitoring device corresponding to the passive monitoring acoustic signals, and entering the step 3.4); if the outlier characteristic vector does not exist, the pipe network pipeline does not leak, the wireless monitoring equipment corresponding to the passive monitoring acoustic signal monitors whether the signal is a leakage signal, and the step 4) is carried out; 3.4) for two adjacent wireless monitoring devices which monitor the leakage signals, calculating the cross correlation coefficient r (m) of the monitored acoustic signals:
Figure BDA0002257082650000042
wherein x issiAnd xsjRespectively representing acoustic signals monitored by two adjacent wireless monitoring devices i and j, wherein t represents time, and m represents a discretely-changed variable; 3.5) determining the position of the pipe network pipeline with leakage according to the calculated cross correlation coefficient r (m), and entering the step 7):
Figure BDA0002257082650000043
wherein L iss1Indicating the distance of the leak from the wireless monitoring device i, c0Represents the propagation speed of sound waves in the pipeline of the pipe network, lsRepresents the distance, m, between wireless monitoring devices i and j0Represents m when r is maximized.
Further, the specific process of step 6) is as follows: 6.1) the data processing cloud end carries out interpretation calculation on each active monitoring sound signal, judges whether the pipe network pipeline is corroded or blocked, and if the pipe network pipeline is not corroded, the data processing cloud end carries out interpretation calculation on each active monitoring sound signalIf corrosion or blockage occurs, updating the pipe network state of the water supply pipe network, and directly entering the step 1); if the pipeline of the pipe network is corroded or blocked, entering the step 6.2); 6.2) calculating the distance L of the corrosion or blockage point from the wireless monitoring device i1：
L1＝t╳c0
Wherein t represents the acoustic signal xI(t) emission time and reflected acoustic signal xR(t) time difference of arrival times; 6.3) calculating the inner diameter D and the length L of the pipeline of the pipe network after corrosion or blockage occurs, and entering the step 7).
Further, the specific process of step 6.1) is as follows: 6.1.1) Each acoustic signal x is modulated according to the voltage response of the hydrophone in each monitoring unitI(t)、xR(t) and xT(t) are all converted into corresponding sound pressure signals pI(t)、pR(t) and pT(t); 6.1.2) to the sound pressure signal pI(t)、pR(t) and pT(t) respectively carrying out Fourier transform to obtain sound pressure levels with different frequencies; 6.1.3) calculating the loss T (f) of the sound pressure level at different frequencies and determining the maximum value T thereofmaxAnd a minimum value TminWherein, the loss T (f) of the sound pressure level at different frequencies is:
Figure BDA0002257082650000051
wherein p isT(f) Representing a sound pressure signal pT(t) sound pressure level at frequency f, pI(f) Representing a sound pressure signal pI(t) sound pressure level at frequency f; 6.1.4) maximum value T if T (f) is lostmaxEqual or approximately equal to the minimum value T of the loss T (f)minIf the pipeline of the pipe network is not corroded or blocked, updating the pipe network state of the water supply pipe network, and entering the step 1); maximum value T if loss T (f)maxGreater than the minimum value T of the loss T (f)minAnd 6.2) if the pipeline of the pipe network is corroded or blocked.
Further, the specific process of step 6.3) is as follows: 6.3.1) calculating the inner diameter D of the pipe network pipeline after corrosion or blockage:
Figure BDA0002257082650000052
wherein d represents the inner diameter of the pipeline of the pipe network without blockage or corrosion, and the parameter
Figure BDA0002257082650000053
Minimum value T of loss T (f)min＝TI,min，TI,minIs the minimum value of the transmission coefficient;
6.3.2) calculating the length L of the corroded or blocked water supply pipe network, and entering the step 7):
Figure BDA0002257082650000054
wherein k represents a positive integer, fminMinimum value T representing loss T (f) of sound pressure level at different frequenciesminThe corresponding frequency.
By adopting the technical scheme, the invention has the following advantages: the intelligent water supply pipe network monitoring system is provided with a wireless monitoring device and a data processing cloud end, the damage and leakage of the water supply pipe network pipeline are monitored in a passive monitoring mode, and the corrosion or blockage in the pipe is identified in an active monitoring mode. Passive monitoring employs conventional autocorrelation algorithms to identify pipeline damage leakage information. In the active monitoring process, the corrosion or blockage of the pipeline is generalized into an expansion pipe or a contraction pipe with a sudden change of section to form a pipeline silencer, and the size and the position of the corrosion or blockage are calculated by introducing the acoustic principle of the pipeline silencer. Active monitoring can be achieved by transmitting and receiving acoustic signals for interpretation, and the problem that water supply is seriously influenced by the existing method can be solved. The invention adopts a combination mode of active and passive monitoring, can combine the advantages of two monitoring methods, simultaneously realizes the monitoring of pipeline damage leakage, internal corrosion or blockage, has higher use value, and can be widely applied to the field of water supply systems.
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FIG. 1 is a schematic diagram of the monitoring system of the present invention;
FIG. 2 is a schematic diagram of a wireless monitoring device in the monitoring system;
FIG. 3 is a flow chart of a monitoring method of the present invention;
FIG. 4 is a schematic view showing clogging or corrosion in a water supply network according to an embodiment of the present invention, wherein FIG. 4(a) is a schematic view showing irregular clogging or corrosion in the water supply network, and FIG. 4(b) is a schematic view showing a schematic view of the irregular clogging or corrosion in FIG. 4(a) generalized into a rectangular configuration;
fig. 5 is a time domain diagram of 7 sets of passively monitored acoustic signals in an embodiment of the present invention, where the abscissa is time(s) and the ordinate is sound pressure level (dB);
FIG. 6 is a time domain and frequency domain plot of an emitted acoustic signal in an embodiment of the present invention, where FIG. 6(a) is a time domain plot and FIG. 6(b) is a frequency domain plot;
FIG. 7 is a time domain and frequency domain plot of a reflected acoustic signal in an embodiment of the present invention, where FIG. 7(a) is a time domain plot and FIG. 7(b) is a frequency domain plot;
fig. 8 is a time domain and frequency domain diagram of a transmitted acoustic signal according to an embodiment of the present invention, where fig. 7(a) is a time domain diagram and fig. 7(b) is a frequency domain diagram.
Detailed Description
The present invention is described in detail below with reference to the attached drawings. It is to be understood, however, that the drawings are provided solely for the purposes of promoting an understanding of the invention and that they are not to be construed as limiting the invention.
As shown in fig. 1 and fig. 2, the water supply network condition monitoring system provided by the present invention includes a wireless monitoring device 1, a data processing cloud 2, and a control end 3, wherein the control end 3 may be a computer or a mobile phone.
A plurality of wireless monitoring devices 1 interval sets up on the node of pipe network pipeline 4, each wireless monitoring device 1 all includes monitoring devices 11, communication device 12, power supply unit 13 and controller 14, monitoring devices 11 are used for the quality of water of the interior corresponding node of real-time supervision pipe network pipeline 4, pressure and/or flow signal, and to the acoustic signal of launching acoustic signal in the pipe network pipeline 4 and monitoring pipe network pipeline 4 and corresponding the node, and send the signal of monitoring to data processing high in the clouds 2 through corresponding communication device 12, controller 14 is used for controlling opening or closing of corresponding monitoring devices 11 and communication device 12, power supply unit 13 is used for supplying power for each consumer of corresponding wireless monitoring device 1.
The data processing cloud end 2 is used for determining the pipe network state of each node of the water supply pipe network according to the signals monitored by each monitoring device 11 in real time and a preset pipe network state range, wherein the pipe network state comprises an operation state, a pipe noise intensity and a pipe network pipeline state, and the pipe network state range comprises a water quality range, a flow range, a pressure range and a noise range.
The control end 3 is used for obtaining a monitoring instruction of each monitoring device 11 according to the determined pipe network state at each node of the water supply network, updating the pipe network state of the water supply network, and then sending the monitoring instruction to the corresponding controller 14 through the corresponding communication device 12 through the data processing cloud end 2, so that each controller 14 controls the corresponding monitoring device 11 to perform monitoring operation according to the corresponding monitoring instruction, wherein the monitoring instruction comprises the steps of starting monitoring, ending monitoring, monitoring time, monitoring frequency and the like.
In a preferred embodiment, each monitoring device 11 includes a hydrophone 111, the hydrophone 111 is configured to emit an acoustic signal into the pipe network pipeline 4 and monitor an acoustic signal in the pipe network pipeline 4, each monitoring device 11 further includes a water quality sensor, a pressure sensor and/or a flow sensor, the water quality sensor is configured to monitor a water quality signal (e.g., pH, TDS, etc.) at a corresponding node of the pipe network pipeline 4, the pressure sensor is configured to monitor a pressure signal at a corresponding node of the pipe network pipeline 4, and the flow sensor is configured to monitor a flow signal at a corresponding node of the pipe network pipeline 4.
In a preferred embodiment, each power supply device 13 includes a power generation unit and a battery unit, a plurality of screw holes are opened on the pipe network pipeline 4 corresponding to the positions of the nodes, a turbine 131 is disposed on each power generation unit, each turbine 131 penetrates through the corresponding screw hole and goes deep into the pipe network pipeline 4, and the power generation unit is configured to convert mechanical energy of water flow in the pipe network pipeline 4 into electric energy through the turbine 131 to supply power to each power consumption component of the wireless monitoring device 1. The battery unit is connected with the corresponding controller 14 and is used for supplying power to each electric component of the wireless monitoring device 1 when the power provided by the power generation unit is insufficient. In addition, the power generation unit may charge the battery unit when the power supplied by the power generation unit exceeds the power required by the wireless monitoring device 1.
In a preferred embodiment, each wireless monitoring device 1 includes two monitoring states, namely a quiet period and an active period, and in the quiet period, the wireless monitoring device 1 only monitors the acoustic signals in the pipe network 4; in an active period, the wireless monitoring device 1 immediately monitors the acoustic signal in the pipe network pipeline 4 after transmitting the acoustic signal with certain frequency and strength (which can be set according to actual conditions), wherein the acoustic signal in the pipe network pipeline 4 monitored after the wireless monitoring device 1 transmits the acoustic signal with certain frequency and strength in the active period is an active monitoring acoustic signal, and the acoustic signal in the pipe network pipeline 4 monitored by the wireless monitoring device 1 in a silent period is a passive monitoring acoustic signal.
In a preferred embodiment, an operation state determining module, a pipe noise intensity determining module and a pipe network pipeline state determining module are arranged in the data processing cloud 2. The operation state determination module is used for determining the operation state of the water supply network according to the water quality signal, the pressure signal and/or the flow signal in the pipe network pipeline 4 monitored by the wireless monitoring device 1 and the preset water quality range, the preset pressure range and/or the preset flow range. The in-pipe noise intensity determination module is used for determining the in-pipe noise intensity of the pipe network pipeline 4 according to the passive monitoring acoustic signal monitored by the wireless monitoring equipment 1 and a preset noise range. The pipe network pipeline state determining module is used for determining the pipe network pipeline state of the pipe network pipeline 4 according to the active monitoring acoustic signal and the passive monitoring acoustic signal monitored by the wireless monitoring device 1. Namely whether pipe network pipeline 4 is corroded or blocked, the size and the position of the corrosion or the blockage, and whether pipe network pipeline 4 leaks and the position of the leakage. The pipe section with the pipe network blockage or corrosion is generalized into an expansion pipe or a contraction pipe with a sudden change of section to form a pipe silencer, the acoustic principle of the pipe silencer is introduced into the pipe network pipe state calculation process, and the blockage or corrosion size and position of the pipe network pipe 4 are determined by using an active monitoring acoustic signal. And determining whether the pipe network pipeline 4 leaks and the position of the leakage by utilizing the passive monitoring acoustic signal through a traditional cross-correlation algorithm.
In a preferred embodiment, the pipe network pipes 4 can be cast iron pipes, stainless steel pipes, nodular cast iron pipes, or the like.
Based on the water supply network state monitoring system, as shown in fig. 3, the invention further provides a water supply network state monitoring method, which comprises the following steps:
1) the monitoring period starts, passive monitoring starts, the wireless monitoring device 1 enters a quiet period, one or more monitoring devices 11 are in a monitoring state, and only the hydrophone 111 in each monitoring device 11 monitors the acoustic signal x existing at the corresponding nodes(t) acoustic signal x monitored at this times(t) is the passive monitoring acoustic signal xs(t)。
2) The data processing cloud 2 monitors the acoustic signal x passivelys(t) judging the noise intensity in the pipe of the water supply pipe network within a preset noise range, and entering the step 3 if the noise intensity in the pipe is larger than the preset noise range; and if the intensity of the noise in the pipe is not greater than the preset noise range, entering the step 5):
2.1) separately calculating each passively monitored acoustic signal xsPower P of (t):
Figure BDA0002257082650000081
where T denotes the signal period, p0Denotes the density of water, c0Representing the speed of sound waves propagating in water.
2.2) comparing the calculated power P with a predetermined noise range P0Comparing, if the calculated power P is larger than the noise range P0Entering step 3); if the calculated power P is less than the noise range P0Step 5) is entered, wherein the noise range P is entered0＝S*Iref，IrefRepresenting a reference sound intensity, typically 10-12W/m2(ii) a S represents an area in m2。
3) Data processing cloud 2 monitors each passive acoustic signal xs(t) all the steps are interpreted and calculated to determine whether the pipe network pipeline 4 leaks or not, and if the pipe network pipeline 4 does not leak, the method is implementedIf leakage occurs, entering step 4); if the pipe network pipeline 4 leaks, determining the position of the leakage, and entering the step 7), specifically:
3.1) data processing cloud 2 passively monitoring acoustic signals x according to monitorings(t) calculating Kurtosis factor (Kurtosis) of the passive monitoring acoustic signal, and comparing the Kurtosis factor with the Kurtosis factor (Kurtosis) of the passive monitoring acoustic signal xs(t) performing empirical mode decomposition, calculating the mean square error (rms of imf1, rms of imf2, rms of imf3, rms of imf4, rms of imf5 and rms of imf6) and information entropy (entry of imf1, entry of imf2, entry of imf3, entry of imf4, entry of imf5 and entry of imf6) of the eigenmode functions of the first 6 decompositions, and monitoring passive monitoring acoustic signal xs(t) respectively carrying out Fourier transform (FFT) to obtain average power density (Mean power Spectral density) and frequency centroid (Spectral central), obtaining 15 characteristic values in total, and representing the characteristic vector feature (i) composed of the 15 characteristic values to represent the passive monitoring acoustic signal xs(t)：
Feature(i)
＝[rms of imf1，rms of imf2，rms of imf3，rms of imf4，rms of imf5，rms of imf6，entropy of imf1，entropy of imf2，entropy of imf3，entropy of imf4，entropy of imf5，entropy of imf6，Kurtosis，Mean power spectral density，Spectral centroid] (2)
Where feature (i) represents a feature vector of the passively monitored acoustic signal i.
3.2) because the units and the scales of the characteristic values are inconsistent, normalizing the characteristic values to obtain a normalized passive monitoring sound signal feature (i)kWherein, the normalization processing process is as follows:
Figure BDA0002257082650000091
Figure BDA0002257082650000092
wherein, feature (i)kThe kth characteristic value of the normalized passive monitoring acoustic signal corresponding to the wireless monitoring device i is represented, y represents an intermediate variable, FeaturekMean value representing the kth feature of passively monitored acoustic signals, feature (i)kRepresents the value of the kth characteristic of the passive monitoring acoustic signal i, r represents the optional parameter, and sigmakRepresenting the variance of the kth eigenvalue.
The distance between feature vectors is represented by cosine similarity:
Figure BDA0002257082650000093
wherein feature (j) is a feature vector,
Figure BDA0002257082650000094
Figure BDA0002257082650000095
3.3) carrying out k-means clustering on the normalized passive monitoring acoustic signals, judging whether an outlier characteristic vector exists, if so, leaking a pipe network pipeline 4, and entering the step 3.4 if the acoustic signals monitored by the wireless monitoring equipment 1 corresponding to the passive monitoring acoustic signals are leakage signals; if the outlier characteristic vector does not exist, the pipe network pipeline 4 does not leak, the acoustic signal monitored by the wireless monitoring device 1 corresponding to the passive monitoring acoustic signal is not a leakage signal, and the step 4) is carried out. As the leakage of the water supply network is a few fault events, the leakage signal corresponds to the outlier eigenvector, the passive monitoring acoustic signal corresponding to the outlier eigenvector is the leakage signal, and the corresponding wireless monitoring device 1 monitors the leakage signal.
3.4) for two adjacent wireless monitoring devices 1 which monitor leakage signals, calculating the cross correlation coefficient r (m) of the monitored acoustic signals:
Figure BDA0002257082650000096
wherein x issiAnd xsjRespectively, the acoustic signals monitored by two adjacent wireless monitoring devices i and j, t represents time, and m represents a discretely-varying variable.
3.5) determining the position of the pipe network pipeline 4 with leakage according to the calculated cross correlation coefficient r (m), and entering the step 7):
let m be m when r is maximized0Then the distance L between the leakage point and the wireless monitoring equipment is1Comprises the following steps:
Figure BDA0002257082650000097
wherein, c0Represents the propagation speed l of sound waves in the pipe network pipeline 4sRepresenting the distance between wireless monitoring devices i and j.
4) The water quality sensor, the pressure sensor and/or the flow sensor of each monitoring device 11 monitors the water quality signal, the pressure signal and/or the flow signal at the corresponding node in the pipe network pipeline 4, and compares the water quality signal, the pressure signal and/or the flow signal with a preset water quality range, a preset pressure range and/or a preset flow range, if any signal exceeds the corresponding preset range, the running state of the water supply pipe network is abnormal, and the step 7 is carried out); and if each signal does not exceed the corresponding preset range, the running state of the water supply network is normal, the pipe network state of the water supply network is updated, and the step 1) is directly carried out.
5) When the active monitoring is started, the wireless monitoring device 1 enters an active period, one or more monitoring devices 11 are in a transmitting state, and the hydrophone 111 in each monitoring device 11 transmits an acoustic signal x with a certain frequency and intensityI(t) then, it starts monitoring the reflected acoustic signal xR(t), the adjacent hydrophone 111 then begins monitoring the transmitted acoustic signal xT(t) reflected acoustic signal x at this timeR(t) and a transmitted acoustic signal xTAnd (t) is the active monitoring acoustic signal.
6) The data processing cloud end 2 performs interpretation calculation on each active monitoring sound signal, determines whether the pipe network pipeline 4 is corroded or blocked, and if the pipe network pipeline 4 is not corroded or blocked, updates the pipe network state of the water supply pipe network and directly enters the step 1); if the pipeline 4 of the pipe network is corroded or blocked, determining the size and the position of the corrosion or the blockage, and entering a step 7), specifically:
6.1) the data processing cloud end 2 carries out interpretation calculation on each active monitoring acoustic signal, judges whether the pipe network pipeline 4 is corroded or blocked, and if the pipe network pipeline 4 is not corroded or blocked, updates the pipe network state of the water supply pipe network and directly enters the step 1); and (4) if the pipeline 4 of the pipe network is corroded or blocked, entering a step 6.2):
6.1.1) Acoustic Signal xI(t) after propagation loss, transmission and reflection in the pipe network pipeline 4, a reflected acoustic signal x is formedR(t) and a transmitted acoustic signal xT(t) converting each acoustic signal x according to the voltage response of each hydrophone 111I(t)、xR(t) and xT(t) are all converted into corresponding sound pressure signals pI(t)、pR(t) and pT(t)。
6.1.2) to the sound pressure signal pI(t)、pR(t) and pTAnd (t) respectively carrying out Fourier transform to obtain sound pressure levels of different frequencies.
6.1.3) calculating the loss T (f) of the sound pressure level at different frequencies and determining the maximum value T thereofmaxAnd a minimum value TminWherein, the loss T (f) of the sound pressure level at different frequencies is:
Figure BDA0002257082650000101
wherein p isT(f) Representing a sound pressure signal pT(t) sound pressure level at frequency f, pI(f) Representing a sound pressure signal pI(T) sound pressure level at frequency f, loss T (f) being a frequency-dependent value having a maximum value TmaxMinimum value of TminCorresponding to frequencies respectively of fmaxAnd fmin。
6.1.4) maximum value T if T (f) is lostmaxEqual or approximately equal to the minimum value T of the loss T (f)minIf the pipe network pipeline 4 is not corroded or blocked, updating the pipe network state of the water supply pipe network, and entering the step1) (ii) a Maximum value T if loss T (f)maxGreater than the minimum value T of the loss T (f)minAnd then the pipe network pipeline 4 is corroded or blocked, and the step 6.2) is carried out.
6.2) calculating the distance L of the corrosion or blockage point from the wireless monitoring device i1：
As shown in FIG. 4, irregular corrosion or blockage (reference numeral 1 in FIG. 4) inside pipe network 4 is generalized to a rectangular structure (reference numeral 2 in FIG. 4), and an acoustic signal xI(t) emission time and reflected acoustic signal xR(t) time difference of arrival time t, distance L of corrosion or blockage point from wireless monitoring device i1Comprises the following steps:
Figure BDA0002257082650000111
6.3) calculating the inner diameter D of the pipe network pipeline 4 after corrosion or blockage:
when the sound signal passes through the structure shown in fig. 4, the section of the pipe network pipeline 4 is suddenly changed, and the sound basic principle can deduce that the transmission coefficient T of the sound wave passes through the sudden change structureIComprises the following steps:
Figure BDA0002257082650000112
wherein λ represents an acoustic wavelength; l represents the length of the pipeline 4 subjected to corrosion or blockage; parameter σ ═ S0/S1，S0＝πD2(ii)/4, represents the area of the pipe 4 in the pipe network where corrosion or clogging occurs, S1＝πd2The area of the pipe network pipeline 4 after corrosion or blockage is represented by/4, and D, d represents the inner diameter of the pipe network pipeline 4 after corrosion or blockage and the inner diameter of the pipe network pipeline 4 which is not blocked or corroded respectively; minimum value T of transmission coefficientI,minComprises the following steps:
Figure BDA0002257082650000113
theoretical maximum of transmission coefficientThe value should be 1, however, there may be noise in the pipe network 4, resulting in TI,maxIs greater than 1. Let TI,min＝TminAnd then:
Figure BDA0002257082650000114
the inner diameter D of the pipe network pipeline 4 after corrosion or blockage is as follows:
Figure BDA0002257082650000115
6.4) calculating the length L of the pipeline 4 with the corrosion or the blockage of the pipe network, and entering the step 7):
frequency f corresponding to the minimum loss of sound pressure level at different frequenciesminCorresponding wavelength is lambdaminIn this case, the condition for minimizing the loss is:
Figure BDA0002257082650000116
the length L of the pipe network 4 which is corroded or blocked is as follows:
Figure BDA0002257082650000117
wherein k represents a positive integer, and can be determined according to the actual situation of the pipe network pipeline 4, and generally takes 1.
7) After the control end 3 obtains a monitoring instruction (for example, ending monitoring so that a worker can start maintenance work) of each monitoring device 11 according to the determined pipe network state at each node of the water supply network and updates the pipe network state of the water supply network, the monitoring instruction is sent to the corresponding controller 14 through the corresponding communication device 12 through the data processing cloud end 2, and each controller 14 controls the corresponding monitoring device 11 to perform monitoring operation according to the corresponding monitoring instruction, and then the step 1 is performed.
In step 1), the data transmitted by the monitoring device 11 in the monitoring state to the data processing cloud 2 through the communication module at least includes: the acoustic signals present in the water supply network, the number and position of the monitoring devices 11, the monitoring time and the monitoring mode (active monitoring or passive monitoring).
In step 6), the data transmitted by the monitoring device 11 in the transmitting state to the data processing cloud 2 through the communication module at least includes: the acoustic signal emitted by the monitoring device 11, the number and location of the monitoring device 11, the time of emission, and the manner of monitoring (active or passive).
The method for monitoring the condition of a water supply network according to the present invention will be described in detail below with reference to specific examples.
Simulation calculation of passive monitoring:
as shown in FIG. 5, the signals x of 7 groups monitored by the wireless monitoring devices 1-7 in a certain passive monitoring processs1(t)～xs7(t), wherein the wireless monitoring devices 1 and 2 monitor leakage signals, the wireless monitoring devices 3-7 monitor noise signals, the distance between the wireless monitoring devices 1 and 2 is 100m, a leakage point is located between the wireless monitoring devices 1 and 2, and the distance between the leakage point and the wireless monitoring device 1 is 12 m.
Obtaining a feature vector of the passive monitoring acoustic signal through feature extraction and normalization processing, for example, the feature vector of the passive monitoring acoustic signal 1 is:
Feature(1)＝(0.4400 0.4400 0.4400 0.4400 0.4400 0.4400 0.4418 0.4418 0.4415 0.4418 0.4418 0.4418 0.4429 0.3719 0.9735)
and performing k-means clustering on the normalized feature vectors of the 7 groups of passive monitoring acoustic signals, judging outlier feature vectors, finding that the passive monitoring acoustic signal 1 and the passive monitoring acoustic signal 2 are outlier signals, and judging the outlier acoustic signals to be leakage acoustic signals.
For passively monitoring acoustic signal xs1(t) and passively monitoring the acoustic signal xs2(t) performing cross-correlation calculation to obtain a variable m of discrete change which is 0.05 and the wave speed c of the sound wave in the water0The distance between two wireless monitoring devices 1 is i 1470m/ssThe distance between the leakage point and the wireless monitoring device 1 is calculated to be 13.25m and is 1.25m different from the actual distance, which is 100m, and the basic energy is obtainedThe location of the leak can be accurately estimated.
And (3) simulation calculation of active monitoring:
as shown in fig. 4, there is a pipe network pipeline with a length of 100m and a diameter of 100mm, there is a blocked pipe network pipeline at a distance of 130m from the left-end wireless monitoring device, the inner diameter of the blocked pipe network pipeline is 40mm, the length of the blocked pipe network pipeline is 1m, and now an acoustic signal x with known frequency and intensity as shown in fig. 6 is emittedI(t) a frequency range of 200 to 900Hz, reflecting the acoustic signal xR(t) transmitting the acoustic signal x, as shown in FIG. 7T(t) is shown in FIG. 8.
Calculated according to the method of the invention, t is 0.02s, and the speed c of the sound wave in water is considered01470m/s, the distance L between the blockage or corrosion point and the left-end wireless monitoring device1＝t╳c029.4m, which is different from the actual position 30m where the occlusion occurs by 0.6m, the position where the occlusion occurs can be estimated substantially accurately.
Calculating the transmission coefficient T of the sound wave according to the method of the inventionIAs shown in table 1 below:
table 1: transmission coefficient of sound wave
Figure BDA0002257082650000121
Figure BDA0002257082650000131
Maximum value of transmission coefficient TI,maxIs 1.06, minimum value TI,min0.72, corresponding to frequencies of 730Hz and 350Hz, respectively. And calculating the inner diameter D of the pipe network pipeline after corrosion or blockage to be 43.3mm, and the difference between the inner diameter D and the inner diameter of the pipe network pipeline after actual corrosion or blockage is 3.3mm, so that the inner diameter of the blocked pipe network pipeline can be basically and accurately estimated.
The length L of the pipeline of the pipe network which is corroded or blocked is calculated to be 1.05m, and the difference between the length L of the pipeline of the pipe network which is corroded or blocked and the length 1m of the pipeline of the pipe network which is actually corroded or blocked is 0.05m, so that the length of the pipeline of the pipe network which is corroded or blocked can be basically and accurately estimated.
The above embodiments are only used for illustrating the present invention, and the structure, connection mode, manufacturing process, etc. of the components may be changed, and all equivalent changes and modifications performed on the basis of the technical solution of the present invention should not be excluded from the protection scope of the present invention.

Claims (8)

1. A water supply network state monitoring system is characterized by comprising wireless monitoring equipment, a data processing cloud end and a control end;
the wireless monitoring devices are arranged on nodes of a pipe network pipeline at intervals, each wireless monitoring device comprises a monitoring device, a communication device, a power supply device and a controller, the monitoring devices are used for monitoring water quality, pressure and/or flow signals at the nodes corresponding to the pipe network pipeline in real time, transmitting acoustic signals to the pipe network pipeline and monitoring acoustic signals at the nodes corresponding to the pipe network pipeline, sending the monitored signals to the data processing cloud end through the corresponding communication devices, the controller is used for controlling the monitoring devices and the communication devices to be turned on or off, and the power supply device is used for supplying power to all power utilization parts corresponding to the wireless monitoring devices;
each monitoring device comprises a hydrophone, a water quality sensor, a pressure sensor and/or a flow sensor;
the hydrophone is used for transmitting acoustic signals into the pipe network pipeline and monitoring the acoustic signals in the pipe network pipeline;
the water quality sensor is used for monitoring a water quality signal at a corresponding node of a pipe network pipeline;
the pressure sensor is used for monitoring pressure signals at corresponding nodes of the pipeline of the pipe network;
the flow sensor is used for monitoring flow signals at corresponding nodes of the pipeline of the pipe network;
the data processing cloud end is used for determining the pipe network state of each node of the water supply pipe network according to the signals monitored by each monitoring device in real time and a preset pipe network state range;
the control end is used for obtaining a monitoring instruction of each monitoring device according to the determined pipe network state of each node of the water supply network, updating the pipe network state of the water supply network, and sending the monitoring instruction to the corresponding controller through the corresponding communication device through the data processing cloud end, so that each controller controls the corresponding monitoring device to perform monitoring operation according to the corresponding monitoring instruction;
each wireless monitoring device comprises two monitoring states of a silent period and an active period;
in a silent period, the wireless monitoring equipment only monitors acoustic signals in the pipe network pipeline, wherein the acoustic signals are passive monitoring acoustic signals;
in the active period, the wireless monitoring equipment immediately monitors the acoustic signal in the pipe network pipeline after transmitting the acoustic signal with certain frequency and intensity, and the monitored acoustic signal is an active monitoring acoustic signal.
2. The water supply network condition monitoring system of claim 1, wherein each of said power supply units comprises an electric power generation unit and a battery unit;
the pipe network pipeline is provided with a plurality of screw holes corresponding to the positions of the nodes, each power generation unit is provided with a turbine, each turbine penetrates through the corresponding screw hole to penetrate into the pipe network pipeline, and the power generation unit is used for converting mechanical energy of water flow in the pipe network pipeline into electric energy through the turbine and supplying power to each power utilization part of the wireless monitoring equipment;
the battery unit is connected with the corresponding controller and used for supplying power to each power utilization component of the wireless monitoring equipment when the power generation unit is insufficient in power; in addition, when the power provided by the power generation unit exceeds the power required by the wireless monitoring device, the power generation unit is used for charging the battery unit.
3. The water supply network state monitoring system according to claim 1, wherein the pipe network state comprises an operating state, an in-pipe noise intensity and a pipe network pipeline state, the pipe network state range comprises a water quality range, a flow range, a pressure range and a noise range, and an operating state determining module, an in-pipe noise intensity determining module and a pipe network pipeline state determining module are arranged in the data processing cloud;
the operation state determining module is used for determining the operation state of the water supply network according to the water quality signal, the pressure signal and/or the flow signal monitored by the wireless monitoring equipment and the preset water quality range, the preset pressure range and/or the preset flow range;
the in-pipe noise intensity determination module is used for determining the in-pipe noise intensity of the water supply pipe network according to the passive monitoring acoustic signal monitored by the wireless monitoring equipment and a preset noise range;
the pipe network pipeline state determining module is used for determining the pipe network pipeline state of the water supply pipe network according to the active monitoring acoustic signal and the passive monitoring acoustic signal monitored by the wireless monitoring equipment.
4. A water supply network condition monitoring method based on the water supply network condition monitoring system of claim 3, comprising:
1) when the monitoring period begins, the wireless monitoring equipment enters a silent period, only each monitoring device monitors the acoustic signal existing at the corresponding node, and the monitored acoustic signal is the passive monitoring acoustic signal xs(t)；
2) The data processing cloud respectively calculates each passive monitoring acoustic signal xs(t) comparing the calculated power P with a preset noise range, and entering step 3 if the calculated power P is larger than the noise range; if the calculated power P is less than the noise range, step 5) is entered, wherein the acoustic signal x is passively monitoredsThe power P of (t) is:
Figure FDA0002776186790000021
where T denotes the signal period, p0Denotes the density of water, c0Representing the propagation velocity of sound waves in water;
judging the noise intensity in the pipe of the water supply pipe network, and entering the step 3) if the noise intensity in the pipe is larger than a preset noise range; if the intensity of the noise in the pipe is not larger than the preset noise range, entering the step 5);
3) data processing cloud port is to each passive monitoring acoustic signal xs(t) performing interpretation calculation to determine whether the pipeline of the pipe network leaks, and if the pipeline of the pipe network does not leak, entering the step 4); if the pipeline of the pipe network leaks, determining the position of the leakage, and entering the step 7);
4) the water quality sensor, the pressure sensor and/or the flow sensor of each monitoring device monitors the water quality signal, the pressure signal and/or the flow signal at the corresponding node in the pipe network pipeline 4, and compares the water quality signal, the pressure signal and/or the flow signal with a preset water quality range, a preset pressure range and/or a preset flow range, if any signal exceeds the corresponding preset range, the running state of the water supply pipe network is abnormal, and the step 7 is carried out; if each signal does not exceed the corresponding preset range, the running state of the water supply network is normal, the pipe network state of the water supply network is updated, and the step 1) is directly carried out;
5) when the wireless monitoring equipment enters an active period, each monitoring device transmits an acoustic signal x with certain frequency and intensityI(t) then, it starts monitoring the reflected acoustic signal xR(t) the adjacent monitoring device immediately starts monitoring the transmitted acoustic signal xT(t) reflected acoustic signal x at this timeR(t) and a transmitted acoustic signal xT(t) is the active monitoring acoustic signal;
6) the data processing cloud end carries out interpretation calculation on each active monitoring sound signal, whether a pipe network pipeline is corroded or blocked is determined, if the pipe network pipeline is not corroded or blocked, the pipe network state of the water supply pipe network is updated, and the step 1 is directly carried out); if the pipeline of the pipe network is corroded or blocked, determining the size and the position of the corrosion or the blockage, and entering a step 7);
7) and (3) the control end obtains the monitoring instruction of each monitoring device according to the determined pipe network state, updates the pipe network state of the water supply pipe network, and sends the monitoring instruction to the corresponding controller through the corresponding communication device through the data processing cloud, so that each controller controls the corresponding monitoring device to perform monitoring operation according to the corresponding monitoring instruction, and then the step 1) is carried out.
5. The method for monitoring the condition of the water supply network according to claim 4, wherein the specific process of the step 3) is as follows:
3.1) data processing cloud computing passive monitoring of acoustic signals xs(t) kurtosis factor, passive monitoring of acoustic signal x for monitorings(t) performing empirical mode decomposition, calculating the mean square error and information entropy of eigenmode functions of the previous 6 decompositions, and monitoring the passive monitoring acoustic signal xs(t) respectively carrying out Fourier transform to obtain average power density and frequency centroid, obtaining 15 characteristic values in total, and representing passive monitoring acoustic signal x monitored by wireless monitoring equipment i by characteristic vector feature (i) formed by the 15 characteristic valuess(t)；
3.2) normalizing each characteristic value to obtain a normalized passive monitoring sound signal feature (i)k：
Figure FDA0002776186790000031
Wherein, feature (i)kExpressing the kth characteristic value of the normalized passive monitoring acoustic signal corresponding to the wireless monitoring equipment i, wherein y expresses an intermediate variable;
3.3) carrying out k-means clustering on the normalized passive monitoring acoustic signals, judging whether an outlier characteristic vector exists, if so, leaking a pipe network pipeline, monitoring a leakage signal by a wireless monitoring device corresponding to the passive monitoring acoustic signals, and entering the step 3.4); if the outlier characteristic vector does not exist, the pipe network pipeline does not leak, the wireless monitoring equipment corresponding to the passive monitoring acoustic signal monitors whether the signal is a leakage signal, and the step 4) is carried out;
3.4) for two adjacent wireless monitoring devices which monitor the leakage signals, calculating the cross correlation coefficient r (m) of the monitored acoustic signals:
Figure FDA0002776186790000032
wherein x issiAnd xsjRespectively representing acoustic signals monitored by two adjacent wireless monitoring devices i and j, wherein t represents time, and m represents a discretely-changed variable;
3.5) determining the position of the pipe network pipeline with leakage according to the calculated cross correlation coefficient r (m), and entering the step 7):
Figure FDA0002776186790000033
wherein L iss1Indicating the distance of the leak from the wireless monitoring device i, c0Represents the propagation speed of sound waves in the pipeline of the pipe network, lsRepresents the distance, m, between wireless monitoring devices i and j0Represents m when r is maximized.
6. The method for monitoring the condition of the water supply network according to claim 5, wherein the specific process of the step 6) is as follows:
6.1) the data processing cloud end carries out interpretation calculation on each active monitoring sound signal, judges whether a pipe network pipeline is corroded or blocked, updates the pipe network state of the water supply pipe network if the pipe network pipeline is not corroded or blocked, and directly enters the step 1); if the pipeline of the pipe network is corroded or blocked, entering the step 6.2);
6.2) calculating the distance L of the corrosion or blockage point from the wireless monitoring device i1：
L1＝t╳c0
Wherein t represents the acoustic signal xI(t) emission time and reflected acoustic signal xR(t) time difference of arrival times;
6.3) calculating the inner diameter D and the length L of the pipeline of the pipe network after corrosion or blockage occurs, and entering the step 7).
7. The method for monitoring the condition of the water supply network according to claim 6, wherein the step 6.1) comprises the following specific steps:
6.1.1) Each acoustic signal x is modulated according to the voltage response of the hydrophone in each monitoring unitI(t)、xR(t) and xT(t) are all converted into corresponding sound pressure signals pI(t)、pR(t) and pT(t)；
6.1.2) to the sound pressure signal pI(t)、pR(t) and pT(t) respectively carrying out Fourier transform to obtain sound pressure levels with different frequencies;
6.1.3) calculating the loss T (f) of the sound pressure level at different frequencies and determining the maximum value T thereofmaxAnd a minimum value TminWherein, the loss T (f) of the sound pressure level at different frequencies is:
Figure FDA0002776186790000041
wherein p isT(f) Representing a sound pressure signal pT(t) sound pressure level at frequency f, pI(f) Representing a sound pressure signal pI(t) sound pressure level at frequency f;
6.1.4) maximum value T if T (f) is lostmaxEqual to the minimum value T of the loss T (f)minIf the pipeline of the pipe network is not corroded or blocked, updating the pipe network state of the water supply pipe network, and entering the step 1); maximum value T if loss T (f)maxGreater than the minimum value T of the loss T (f)minAnd 6.2) if the pipeline of the pipe network is corroded or blocked.
8. The method for monitoring the condition of the water supply network according to claim 7, wherein the step 6.3) comprises the following specific steps:
6.3.1) calculating the inner diameter D of the pipe network pipeline after corrosion or blockage:
Figure FDA0002776186790000042
wherein d represents the inner diameter of the pipeline of the pipe network without blockage or corrosion, and the parameter
Figure FDA0002776186790000043
Minimum value T of loss T (f)min＝TI,min，TI,minIs the minimum value of the transmission coefficient;
6.3.2) calculating the length L of the corroded or blocked water supply pipe network, and entering the step 7):
Figure FDA0002776186790000051
wherein k represents a positive integer, fminMinimum value T representing loss T (f) of sound pressure level at different frequenciesminThe corresponding frequency.
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