DK202070157A1 - System and method for acoustic leak detection - Google Patents

Abstract

Method for identifying a leak indication in a utility distribution system including a pipe network for supplying a utility to a multitude of service connections and a plurality of acoustic sensor mounted at the service connections. The method comprises the steps of: determining the presence of a normal fluid pressure in the pipe network; establishing a baseline noise indicator at a time of the normal fluid pressure, using the acoustic sensors; determining the presence of a difference fluid pressure in the pipe network; establishing a leak noise indicator at a time of the difference fluid pressure, using the acoustic sensors; and correlating one or more base line noise indicators and leak noise indicators to determine service connections subject to leak indications.

Description

DK 2020 70157 A1 1 System and method for acoustic leak detection Field of the Invention The present invention relates to a system and methods for identifying leaks in a utility distri- bution system, such as a water distribution system. The system includes a plurality of acoustic sensors configured to measure noise or an acoustic profile of a pipe network. Background of the Invention In distribution networks for potable water or hot water for district heating it is of utmost im- portance to be able to detect leaks quickly after they appear. In water distribution networks not only because scarce drinking water may be lost but also because leaks are a possible source of contamination as the water becomes directly exposed to the surroundings. Several systems exist to detect leaks in distribution networks, including acoustic measurements sys- tems (listening sticks, noise correlators, ground microphones, noise logger systems, etc.), trace gas systems, and SAR radar systems. However, only few of these systems focus on continuous monitoring of the network.

Noise loggers (accelerometers or hydrophones) installed on stop valves or fire hydrants are known and combined with correlation techniques these may be used to analyze data and track network developments over time. However, such logger systems require many logger devices to be installed to cover an entire network and get an optimal coverage of the grid. Such standalone systems are expensive, time consuming to install and must be maintained to work properly. More resent monitoring systems are based on noise measuring being implemented in house- hold smart meters. Such systems benefit from the fact that smart meters may be installed at all service connections and installation and maintenance of the meter-based noise logger sys- tem becomes an integrated part of installation and maintenance of the consumption meter infrastructure. Furthermore, smart meters are often equipped with wireless communication capabilities that can be shared by the noise logger system. Consumption meter based noise loggers or acoustic sensors may however suffer from disad- vantages such as a high level of ambient noise, especially when installed inside a house where ambient noise sources such as consumption flow, circulation pumps, flow noise from district

DK 2020 70157 A1 2 heating, etc. exist.

A need therefor exists for an improved leak detection system based on measurement data from noise loggers or acoustic sensors.

Object of the Invention Itis an objective to provide an improved leak detection system and method for detecting leaks in pipe networks, such as utility distribution networks for water and hot water for district heat- ing.

Further, it is an objective to provide an improved approach for reducing the impact of ambient noise in a system including acoustic noise detectors or sensors.

Description of the Invention The objective is achieved by a method for identifying leak indication in a utility distribution system including a pipe network for supplying a utility to a multitude of service connections and a plurality of acoustic sensors mounted at service connections; the method comprising the steps of: determining the presence of a normal fluid pressure in the pipe network; estab- lishing a baseline noise indicator at a time of the normal fluid pressure, using the acoustic sensors; determining the presence of a difference fluid pressure in the pipe network; estab- lishing a leak noise indicator at a time of the difference fluid pressure, using the acoustic sen- sors; and correlating one or more baseline noise indicators and leak noise indicators to deter- mine service connections subject to leak indications.

The invention thus resides in a method where a signal indicative of an acoustic noise level in the pipes is established during a normal fluid pressure situation and during an amended fluid pressure situation.

The word normal is here to be understood as the state of operation without defects in the pipes such as leaks or without extreme high or low flows generated by consum- ers.

Once the normal acoustic noise level is determined the pressure in an amended or abnor- mal state of the pipe system is measured, i.e. in a state where the pipe pressure deviates from the normal pressure.

The deviating pressure is herein coined difference-fluid-pressure and thus has a pressure amplitude that is different from the normal pressure amplitude under normal operating conditions.

From acoustic noise measurements made in each of these two pressure states a baseline noise indicator and a leak noise indicator is established and a corre- lation of these two indicators makes it possible to make a statement about the presence or not of a leakage in the pipe system.

The correlation is done by comparing sampling data ob- tained at the normal pressure with the sampling data obtained during the difference fluid pressure.

The invention thus utilizes a change in the pipe pressure to detect the presence or not of a leakage.

DK 2020 70157 A1 3 The steps for determining the presence of normal- and difference fluid pressures and estab- lishing baseline- and leak noise indicators may be done as separate or integrated steps.

For example may the baseline noise indicator be established at a time of a normal fluid pressure.

Similar may the leak noise indicator be established at a time of a difference fluid pressure.

Whether the baseline noise indicator is in fact established at a time of normal fluid pressure may not be determined before after the noise measure has been recorded.

This may be done by subsequent correlation or comparison of noise measurements and pressure data relevant to a specific acoustic sensor installed at a service connection.

The same may apply for the leak noise indicator.

Here, the normal fluid pressure may be the standard operating pressure of the distribution system and the difference fluid pressure may be due to a planned and controlled decrease or increase in the operating pressure of the distribution system.

However, the difference pres- sure may also be determined during periods of naturally occurring pressure variations in the distribution system.

According to the invention, a method and system is achieved wherein ambient noise sources are filtered out in a system of acoustic noise sensors included in a utility distribution system.

The method is based on the insight that noise originating from leaks or other system abnor- malities is correlated with the pressure in the system, whereas noise from most ambient noise sources are not.

Regulating fluid or water pressure in a pipe network of a utility distribution system will there- fore change the noise pattern or noise amplitude generated by leaks.

Noise from ambient noise sources will on the other hand remain as before the water pressure was regulated.

Con- trolling the water pressure may thus be used to filter out ambient noise sources such as pumps.

Especially, systems wherein noise detection takes place at the service connection in- side houses will benefit from such approach since such systems often are subject to more am- bient noise sources.

The invention further relates to a leak detection system for identifying leak indication in a utility distribution system including a pipe network for supplying a utility to a multitude of service connections, comprising means for carrying out the above described leak identification

DK 2020 70157 A1 4 method and an acoustic sensor or a smart utility meter including the acoustic sensor, compris- ing communication means configured to receive commands to adjust the noise sampling rate and to transmit a noise indicator to a remote location.

The leak detection system comprises acoustic sensors mounted at a plurality of the service connections and is configured to establish one or more baseline noise indicators and leak noise indicators. The system further comprises one or more pressure sensing devices for determin- ing the fluid pressure in the pipe network; a data collection system for collecting pressure data related to the fluid pressure determined by the pressure sensing device and noise data includ- ing the one or more baseline noise indicators from the plurality of acoustic sensors. A data processing device is configured to correlate the one or more baseline noise indicators and leak noise indicators to determine service connections subject to leak indications.

Filtering out noise from ambient sources having a known frequency requires knowledge about the nature of the different noise sources in comparison with the noise generated from a leak. Also, noise sources may change over time, requiring systems to be constantly updated or based on cloud or back-end data analysis, where raw data is send to a central server. In this regard it is noted that heavy data analysis in edge devices such as smart consumption meters or acoustic sensors may be disadvantageous as it increases current consumption and therefore reduce the battery lifetime. On the other hand, edge computing of measured data is often advantageous over back-end computing of data, as it may reduce data transmissions and thereby reduce power consumption.

Throughout the specification of the current invention the notion of a pipe network is used.

The pipe network may mean the entire pipe network of a utility distribution system or only a section or part of the pipe network of a utility distribution system, which is also sometimes referred to as a pipe sub-network.

In one embodiment a pressure regulation profile or successive changes in pressure may be applied to the entire pipe network or only a part of it. The pressure regulation profile, i.e. knowledge about the changing fluid pressure, may then be correlated with noise measure- ments to look for correlations and identify leak indications or indications about the presence of other abnormalities.

DK 2020 70157 A1 Such a pressure profile or pressure variations could be implemented during night time to min- imize the inconvenience experienced by consumers. However, the pressure variations do not need to be out of the range of normal system operation. Also, the pressure variations or pres- sure profile correlated with noise measurements may be naturally occurring pressure varia- 5 tions occurring in the pipe network. In one embodiment variations in system pressure may be within 75% to 125 % of the standard operation pressure. However in some implementations of the method and system, larger var- iations such as 50% - 150% or 25 - 175% or 0 - 200% may be applied to further improve filtering out of ambient noise sources.

Furthermore, the same or different pressure variation profile could be implemented at regular intervals, such as each night, over a period of time, such as during the course of a week, a month or a year to filter out fluctuations in both ambient noise sources and leak variations. A pressure variation profile may also be implemented continuously in order to implement on- going monitoring of a pipe network. All in all this will improve the probability of determining whether detected noise is caused by an irrelevant ambient noise source or in fact originates from a leak or other abnormality.

The pressure variation profile may have different shapes. During the time period with differ- ence fluid pressure, i.e. the period where the pipe pressure is above or below the normal fluid pressure and where the acoustic noise signal has changed its amplitude compared to its am- plitude during the normal fluid pressure, the pressure can be held at a constant amplitude or have a variable amplitude. For example, in order to avoid water hammer, S curves or linear ramping up or down of the amplitude can be used. The pressure variation profile can also be a pulsed profile with a number of pulsations during the time period of the difference fluid pressure.

The method according to the invention can advantageously be implemented by transferring the noise measurements themselves - or signals indicative of noise levels - to a back end system which processes the data according to the invention. From the back end system in- structions are then given to a speed controlled pump to reduce the pressure or stop pumping all together if an indication of leakage has been established. This is an indirect communication between pump and acoustic sensors.

Alternatively, one or more acoustic sensors may be in direct wired or wireless communication with the pump.

The pump collects the incoming noise data (whether raw or un-processed noise indicators) and processes them by use of its data processing device.

A signal indicative of the pipe pressure can come from an external pressure sensor but a pressure sensor is often integrated in the pump.

After processing the data the pump locally, i.e. by itself, takes the decision to reduce the pipe pressure or stop pumping if receiving or calculating an indication of a leakage.

Electronically speed regulated pumps have either integrated memory and control electronics that will be able to process a method according to the invention locally, or memory and control electronics in a frequency converter connected to and speed controlling the pump will be able to do it.

Description of the drawings In the following embodiments of the invention will be described with reference to the follow- ing figures: Figure 1 illustrates a utility distribution system including a pipe network, Figure 2 illustrates a pipe sub-network of a utility distribution system,

Figure 3 illustrates a method for determining leak indications, Figure 4 illustrates a communication infrastructure for a utility distribution system, Figure 5 illustrates an acoustic sensor for installation at a service connection, Figure 6 illustrates a pressure regulation profile and acoustic sensor sampling times, Figure 7 illustrates naturally ocurring system pressure variations,

Figure 8a and 8b illustrates examples of leak noise power as a function of system pressure, Figure 9 illustrates different scenarios of a utility distribution system subject to varying pres- sures profiles.

DK 2020 70157 A1 7 Detailed description of the invention Fig. 1 illustrates a utility distribution system 1 including a pipe network and a plurality of ser- vice connections 3. The utility distribution system and pipe network may for example be a system for distributing potable water or heated water in a district heat system. The service connections 3 supply residential, commercial or other premises with the respective utility. The pipe network may be divided into a number of pipe sub-networks 21, however this may vary from distribution system to distribution system.

The distribution system shown includes a number of pressure controlling devices 4 arranged through-out the pipe network. Depending on the particulars of a distribution system, including system size and topology, one or more pressure controlling devices may be included. Examples of pressure controlling devices are pumps, pressure reducing control valves or pressure sus- taining valves and the devices are provided in order to ensure that the right pressure is deliv- ered at the service connections. The pressure controlling devices may both be used to control the pressure in the entire pipe network or to control pressure in a pipe sub-network, often referred to as a district metering area (DMA). In one implementation sub-pipe network may be pressure maintained by a pump.

The distribution system further includes a plurality of acoustic sensors 5 (shown in Fig. 2), such as stand-alone smart acoustic sensors or acoustic sensors implemented in smart consumption meters, provided at service connections throughout the system. The acoustic sensor may be provided at all service connections or only at a limited number of the service connections. In case the acoustic sensor is implemented in a smart consumption meter the meter may be installed to measure consumption of the utility supplied through the service connection. The notion of an acoustic sensor is used throughout the specification to mean both a stand-alone smart acoustic sensor or an acoustic sensor implemented in smart consumption meters. By a smart acoustic sensor or consumption meter is meant a device including means providing com- puting power and/or communication means for communicating data to and from external de- vices either wirelessly or via wired connections.

Referring to Fig. 5, an exemplary embodiment of an implementation of an acoustic sensor 5 is shown. The acoustic sensor 5 is adapted for being connected to the pipe network or pipe sub-network 21 and is configured to measure noise or acoustic signals from the fluid flow in

DK 2020 70157 A1 8 the pipe network.

Based on the measurements of noise the acoustic sensor is configured to establish noise indicators, also referred to as baseline noise indicators 51 and leak noise indi- cators 52 as will be further described below.

The noise indicators may be established by a processing unit in the acoustic sensor or in a processing unit in a smart consumption meter in which the sensor is included.

If the acoustic sensor is an integrated part of a smart con-

sumption meter, a common processing unit, also used to determine flow and consumption by the consumption meter, may also be used to establish the noise indicators.

The noise indicator established may comprise one or multiple values determined by the acoustic sensor.

The acoustic sensor may be a dedicated acoustic sensor, such as a trans- ducer including a piezoelectric element, or it may be based on another sensor technology known in the art, such as being a capacitive sensor, an inductive sensor, an optical sensor, or a piezo-resistive sensor, such as a piezoresistive strain gauge.

The acoustic sensor may also be a transducer including a piezoelectric element that is also used for ultrasonic flow meas-

urements, for example according to a time-of-flight principle.

Measuring noise or the acoustic profile using a dedicated acoustic sensor or a transducer used for ultrasonic flow measurements is further described in the earlier published patent application by the applicant, International publication number WO 2017/005687 which is hereby incorporated by reference.

The output from the acoustic sensor is one or more electrical signals, either analog or digital.

To suppress undesired frequencies (such as the mains frequency) or focus on a specific fre- quency band, like 10 - 1000 Hz, analog electrical signals from the acoustic sensor may be electronically filtered.

These electronic filters may be high pass filters, low pass filters, notch filters, comb filters and band pass filters.

The electronical filters may be simple first order RC filters or cascaded versions of such.

Higher order filter types like LCR may also be used.

Fol- lowing the initial electronic filtering, analog evaluation components like peak-detectors, RMS detectors or switchable filters may be implemented resulting in one or a plurality of values indicative of the noise.

DK 2020 70157 A1 9 Following electronic filtering and analog evaluation, the signal may be digitized using an ana- log-to-digital converter (ADC) with a bandwidth chosen to match the bandwidth of the elec- tronic filtering. Alternatively, the analog signal may also be converted from analog to digital without electronic filtering and analog evaluation.

In one embodiment the bandwidth of the ADC is 2 kHz but other bandwidths, such as 200 Hz - 5 kHz may be applied. The overall sampling period may range from approximately 100 milli- seconds (ms) to 1 second or more. In one embodiment the sampling period is approximately 250 ms resulting in a frequency resolution of 4 Hz when the ADC bandwidth is 2 kHz.

Each of the noise indicators 51, 52 may be a collection of raw sampled data, i.e. the data are sent as noise indicators from the acoustic sensor to a remote receiver without any data pro- cessing. It is preferred however, that a reduction of the number of data in the noise indicator is done through digital data processing of the converted output from the acoustic sensor. It may specifically be a simple maximum or a root-mean-square (RMS) calculation to provide a value representing a measure of the overall noise level. E.g. in a selected frequency band, such as 10-1000 Hz. In another example the noise indicators 51, 52 may be the result of a statistical analysis of the raw sampled data including the mean, standard deviation and higher order moments. More sophisticated analysis could also establish the noise indicator through frequency filter- ing into certain frequency bands, followed by an RMS calculation, to provide a range of noise figures associated with different frequency bands. Frequency filtering may also be intro- duced in order to remove unwanted known frequencies like the mains frequency.

Furthermore, a full Fast Fourier Transform (FFT) may be performed to provide a full spec- trum of acoustic signals, involving noise power density as well as associated phase infor- mation. The latter level of analysis may be desirable in order to perform a cross correlation calculation with the purpose of triangulating the location of the noise source. However, for many practical purposes the information coming from the simpler noise figure calculations suffices to indicate the position of the noise source.

DK 2020 70157 A1 10 Throughout all the above described methods for generating noise indicators 51,52 digital fil- tering may be applied. Non-limiting examples are FIR filters and IIR filters. The filter charac- teristic could be high pass filters, low pass filters, notch filters, comb filters and band pass fil- ters. Known undesired frequencies, such as the grid frequency, could also be suppressed in this way.

Also, to create more historical knowledge a long-time-evaluated historic noise measure may be generated from multiple noise indicators created by the acoustic sensor over time. The period between sampling and creating each noise indicator may be substantially longer than the time involved in creating a single noise indicator. Such historic noise measure may be a single value indicative of an average-type noise indicator, i.e. noise level. Furthermore, the acoustic sensor may be arranged to calculate a plurality of spectral values indicative of respective spectral components of average noise level, e.g. corresponding to se- lected frequency bands like 1/1 octave or 1/3 octave levels etc. going towards the full fre- quency spectrum. The acoustic sensor may also be arranged to calculate a peak value indicative of a peak noise level for a period of time. In addition, the acoustic sensor may be arranged to calculate a plu- rality of different values indicative of the noise level for the period of time, these could be statistical parameters such as the mean, RMS-value, the standard deviation or higher order moments. By measuring over a period of time and processing the measured signals in the acoustic sensor, it is possible to reduce the amount of data to be communicated from the acoustic sensor to for example a back-end system.

Hereby both long-time-evaluated historic noise measure/level (calculated from multiple noise indicators acquired over a distribution of time) and/or instantaneous noise indicators (only a single noise indicator) may be provided, the main difference being the time scale in- volved in producing these numbers.

Again referring to Fig. 5, the acoustic sensor 5 further comprises wired or wireless communi- cation means configured to transmit and receive signals, such as activation signals or com- mands, information, data, such as noise indicators 51, 52 etc. to and from a remote location.

DK 2020 70157 A1 11 To collect the noise indicators transmitted by the acoustic sensors and possibly also pressure data from the pressure sensing devices, the utility distribution system includes a data collec- tion system 8, such as an automatic meter reading system (AMR) or an advanced meter in- frastructure (AMI), as illustrated in Fig. 4. Noise indicators and other information, such as consumption data from an integrated smart consumption meter and acoustic sensor, is transmitted from the acoustic sensor 5 to a back-end system 6 for further processing. The back-end system may be implemented in a number of ways as envisaged by the skilled per- son, for example as a cloud service or at server facilities located at the utility providers or at a service provider. The back end system includes a data processing device which by example can be a PLC or a PC work station. Transmission of the noise indicators and possible other in- formation may be effectuated through mobile reading devices 101 for collecting transmis- sions from acoustic sensors (AMR) or through an installed infrastructure 200 (AMI) for col- lecting and forwarding the information to the back-end system 6.

Referring now to Fig. 3, a method 100 for identifying leak indications in the above described utility distribution system will be described. The method includes the step of determining the presence of a normal fluid pressure 110 in the pipe network. The normal fluid pressure may be the standard operating pressure of the distribution system and determination of the nor- mal fluid pressure may include recording the time of the presence of the normal fluid pres- sure. The method also includes a step of determining the presence of a difference fluid pres- sure 130, including the recording of the time of the presence of the difference fluid pressure. The determination of normal and difference fluid pressure may be part of a continuous mon- itoring process tracking the development of the pressure in the distribution system. A time series of naturally occurring pressure data for a distribution system is shown in Fig. 7. How- ever, the pressure in a utility distribution system may also be artificially controlled. Here, the normal fluid pressure may be the standard operating pressure of the distribution system and the difference fluid pressure may be due to a planned and controlled decrease or increase in the operating pressure of the distribution system.

The difference fluid pressure is advantageously obtained by way of variable speed pumps, for example centrifugal pumps. These pumps have integrated control electronics or external controllers regulating their rotational speed and hence the volumetric displacement of fluid

DK 2020 70157 A1 12 in the pipes.

Due to software control of the pumps elaborate pressure profiles can be imple- mented for use in the invention.

A wireless or wired communication link directly between the acoustic sensors and the pumps enables an adaptive and automated leakage detection and also a fast reaction to big leakages — the pump can stop pressurizing the pipe system im- mediately.

Alternatively, instead of the direct communication link, the pumps can be con- trolled from the back-end system 6 (Fig.4). Pressure controlling devices 4, as previously mentioned, may be controlled to generate the required pressure variations for the leak identification method.

Hereby the normal and/or dif- ference pressure may be artificially induced in utility distribution system.

In fact, the pressure may already be reduced by water utilities as part of the daily operation of a distribution sys- tem.

The pressure in the distribution system may for example be reduced during night time to save costs related to pump operation.

In one implementation of the system, a pipe sub-net- work 21 such as a district metering area, may be pressure maintained by a pump.

During night time from for example 01:00 — 03:00 the pressure is lowered from 4 bar to 2.5 bar.

However, the pressure variations may not only be limited to a few hours, pressure variations could also be implied over days.

Fig. 6 illustrates another time series of pressure data for a distribution system (unbroken line). As seen the pressure in the distribution system or pipe sub-network is at 4 bar until for exam- ple 01:00 at which point the pressure is reduced to 2.5 bar before being raised again to 4 bar at 03:00. To be able to use such induced pressure variation as part of the leak identification method, acoustic sensors must in step 120 (Fig.3) perform at least one and preferably more leak noise measurements during the time of the difference fluid pressure i.e. during the period the pressure is reduced to 2.5 bar in the specific example.

As envisaged by the skilled person other distribution system pressures may also be induced.

The step of establishing the leak noise indicator 52 at a time of the difference fluid pressure may be achieved using a number of different sampling strategies.

Fig. 6 illustrates two different strategies.

One being obtaining acoustic data at a fixed frequency (illustrated by crosses) with a constant period of time be- tween each measurement.

Another is a dynamic strategy (illustrated by dots) wherein the measurement of acoustic data are established with a varying frequency such that the fre- quency is higher during the period of difference fluid pressure.

As the pressure is only reduced for a limited period of time, increasing the frequency ensures that more data points are col- lected to improve the data foundation.

During the relative longer period of higher or normal

DK 2020 70157 A1 13 fluid pressure the acoustic sensors must in step 140 perform at least one and preferably more measurements to establish a baseline indicator 51. The sampling frequency during the normal pressure situation can be lower as more time is available to establish these data, the baseline indicator 51.

The leak identification method thus includes the steps of establishing baseline noise indicators 120 at times of normal fluid pressure and acts of establishing leak noise indicator 140 at times of difference fluid pressure. As stated above, to be able to determine normal and leak noise indicators, the leak identification method also includes the step of determining a normal fluid pressure and difference fluid pressure and/or a change in fluid pressure. The step of deter- mining a normal fluid pressure and difference fluid pressure and/or a change in fluid pressure may be done in each or some of the acoustic sensors or on system level as part of data pro- cessing in the back-end system.

The absolute pressure does not necessarily need to be known, only knowledge about changes in pressure are required to establish periods of normal and difference fluid pressure. In an implementation wherein natural pressure variation are relied upon for the leak identification method, the changes in fluid pressure on a relative scale must be monitored. Such information could be obtained by including one or more pressure sensing devices 7 in the distribution sys- tem. It is also necessary to track which pressure state a noise indicator corresponds to, i.e. whether a noise indicator is established during a period of normal fluid pressure or a period of difference pressure. To achieve this noise indicators may be time stamped by the acoustic sensor and compared to pressure data collected from the pressure sensing devices monitoring the distribution system. In another embodiment the acoustic sensor or smart consumption meter with integrated acoustic sensor may be provided with a pressure sensing device, where by at least a relative pressure can be recorded for each noise indicator established.

If the baseline noise indicator is to be established using a dynamic sampling rate as illustrated by the dots in Fig. 6, it is necessary to be able to time the increase in sampling frequency with the time of the artificially induced pressure reduction. To achieve this, one embodiment of the acoustic sensor is provided with 2-way wireless radio communication means whereby a re- quest or command may be transmitted to the acoustic sensor to increase the sampling fre- quency.

DK 2020 70157 A1 14 The sampling strategy applied by the acoustic sensor may also be adapted according to the communication capabilities of the acoustic sensor and the available communication infrastruc- ture. If the acoustic sensor and/or communication infrastructure is only configured to allow transmission of data from the acoustic sensor, but no data or commands to be transmitted to the acoustic sensor, a predefined sampling profile must be applied. Such sampling profile could be based on a constant frequency or a dynamic frequency where the sampling frequency is increased in specific time periods, such as during night time or on specific weekdays as illus- trated in Fig. 6.

Also, the acoustic sensor may include a short range optical communication device providing an interface for changing the sampling strategy locally. Acoustic sensors including 2-way wire- less radio communication means could change sampling strategy on demand from a back-end system. When the pressure profile is planned all acoustic sensors are informed over the 2-way communication link to change their sampling strategies during the time of the pressure profile (illustrated by the dots in Fig. 6). The sampled data can then either be transmitted live or be stored locally. If the data is stored locally it can be send to a back-end system in one or more larger data packages. Alternatively, data processing including various calculations can be done by the acoustic sensor based on information about respective pressure profile applied during sampling of the processed data. Subsequently, the acoustic sensor may send the results of the data processing, such as one or more statistical variables, to the back-end system.

Further, acoustic indicators established by an acoustic sensor can be send continuously to the back-end system or stored locally and send to the back-end system in data packages contain- ing multiple measurements.

As mentioned above it is advantageous if the sampling frequency of obtaining noise indicators is higher or at least comparable to the frequency in pressure variations, such that at least one noise indicator is obtained for each level of pressure. However, a lower sampling frequency may also be implemented if the same changes in pressure, i.e. the same pressure profile, are implemented multiple times and possibly combined with dithering of the sampling time or times of establishing noise indicators.

Referring to Fig. 8a and 8b, an example of a relation between the development in noise power and pipe network pressure or pipe sub-network pressure is illustrated. Each of the charts plot

DK 2020 70157 A1 15 noise measurements representing noise power resulting from a system leak and an ambient noise power originating from a pump against system pressure, i.e. the pressure in the fluid pipes. The vertical axis show the power of the noise signal, here shown in arbitrary units. Fig. 8a and 8b show noise measurements from two different installations, but the tendency of increased noise, i.e. noise power generated from a system leak as a function of a pressure increase, is the same (black dots in the figures). The ambient noise power shown with asterisks is relatively constant and not affected by the increase in pressure. This suggests that noise power from pipe network - or pipe sub-network leaks may be extracted by considering noise power at varying pressure levels and correlating the measurements.

In this regard it is noted that pressure changes may change both the total radiated noise power of aleak and but also the frequency of the radiated noise. Therefore, both the changes in noise power and the changes in the frequency composition of the noise may be determined and analyzed. However, the strongest correlation is often seen with respect to total radiated power and to a less degree frequency changes. Therefore, pressure variations in the pipe net- work or sub-network allows for the implementation of a more simple data analysis, such as an RMS value, into the acoustic sensor since it will be possible to detect the influence of the pres- sure change on the noise power and thus the noise indicators. Simpler data analysis is advan- tageous in the acoustic sensor since it reduces the need for processing power and thus lowers power consumption and improves sensor battery lifetime. Referring to Fig. 3, baseline noise indicators, leak noise indicators and pressure measurements are correlated in step 150 to determine service connections subject to leak indications. Noise measurements and pressure data may be processed by the acoustic sensor it-self or on system level in the back-end system to perform the correlation 150 and leak indication identification. As described above, the noise power registered by the acoustic sensor when subject to higher pressure, will usually be higher compared to when the acoustic sensor is subject to lower power. However, this may not always be the case. In terms of identifying leak indications by correlation of noise and pressure information, the most interesting thing is whether the noise indicators representing the noise power varies with varying pressure. In one embodiment of the leak identification method for identifying leak indication, the base- line noise indicators from a plurality of acoustic sensors of a pipe network are compared to a

DK 2020 70157 A1 16 predetermined noise threshold. If the baseline noise indicator determined is above the noise threshold the noise level is considered abnormal which may be a first indication of a leak indi- cation. If the baseline noise power is below the noise threshold the noise level is considered normal.

As described above, the noise indicator could be a single noise number indicating the noise at the site, such as a peak value or a RMS-value, however it could also be more advanced with specific frequencies weighed and taken into account. It can also be raw, unprocessed data. The noise indicator may be based on the latest noise measurements or include historical noise measurements from the previous day, week , month or year. Fig. 9 illustrates a pipe sub-system 21 subject to a difference i.e. lower pressure (right hand side figure) and a normal i.e. higher pressure (left hand side figure), respectively. The pipe sub- system includes a number of acoustic sensors (illustrated by the small dots) and whether the level of noise power measured by each acoustic sensor is normal or abnormal is illustrated by the size of the dot 92. As seen from the figures, the left hand side figure has five acoustic sensors provided with an abnormal noise level indication 92 and the right hand side figure has only three provided with an abnormal noise level indication 92 . Following the reduction in pressure from the one scenario to the other, the noise indicator determined by two acoustic sensors have thus changed indicating a correlation between the noise power and system pres- sure at these installation. As described above, this may be an indication of a leak. In a pipe system or pipe sub-system including a plurality of acoustic sensors, a noise threshold may be applied to all acoustic sensors such that the acoustic sensors/installations having an abnormal noise level can be identified and subjected to further analysis. The noise threshold could be a global value, determined based on noise indicators from all acoustic sensors in a pipe system. The noise threshold could also be based on noise indicators from a percentage of the sensor population such as 90%, disregarding the sensors representing the 10% the high- est and /or lowest noise indicators. The noise threshold can also be determined in more ad- vanced ways based on statistical parameters of the actual noise indicators in the population, such as the minimum, maximum, mean, standard deviation or higher order moments. The noise threshold could also be set based on experience and measurements from different pipe systems gathered over time.

DK 2020 70157 A1 17 In one embodiment of the method for determining service connections subject to leak indica- tions, the step of correlating baseline noise indicators, leak noise indicators and pressure measurements may include correlating data from the acoustic sensors above the noise thresh- old only. Only these acoustic sensors may then be included in the analysis during the pressure variation, and data collection may in some embodiments be limited to these acoustic sensors. As described above, part of the correlation process may include determining changes in noise indicators during pressure variations. A change in the noise indicator above a predetermined level, such from 20% to 50% or more during the pressure variations may be a good indication that the noise power is due to a leak in the pipe system. A noise indicator may thus be consid- ered to have changed if the level of the difference between the baseline noise indicator and the leak noise indicator is more than 20%, i.e. if the noise measure varies more than 20% dur- ing pressure variations in the pipe system or sub-system. The percentage change in noise in- dicator required to determine a noise indicator change may also be set as a percentage related to the change in pressure. Also, to improve the analysis the statistical behavior of the noise indicator at a specific service connection may be taken into account. Especially the standard deviation may be relevant. In this way the significance of the change in noise indicator can be evaluated.

Another more calculation heavy embodiment, the step of correlating baseline noise indicators, leak noise indicators and pressure measurements may be carried out without the application of the noise threshold. In this embodiment data from acoustic sensors at all or substantially all service connections may be evaluated for changes during the pressure variation. Here again the same percentages as mentioned in relation to the other embodiments may be applied to determine a noise indicator change. Furthermore, the correlation step may include analysis in the frequency domain. As an alter- native or supplement to the noise threshold, a frequency threshold may be applied. For exam- ple frequency peaks in the frequency spectrum below 100 Hz may be monitored and if these change 5%, 10% or more it indicates that the noise is due to a leak. The embodiments of the invention described may be combined in different ways.

Claims (12)

DK 2020 70157 A1 18 CLAIMS

1. Method for identifying leak indication in a utility distribution system (1) including a pipe network for supplying a utility to a multitude of service connections (3), a plurality of acoustic sensors (5) mounted at the service connections, and a pressure sensing device (7); the method comprising the steps of: - determining the presence of a normal fluid pressure (110) in the pipe network, using the pressure sensing device; - establishing (120) a baseline noise indicator (51) at a time of the normal fluid pressure, using the acoustic sensors (5); - determining the presence of a difference fluid pressure (130) in the pipe network, using the pressure sensing device; - establishing (140) a leak noise indicator (52) at a time of the difference fluid pressure, using the acoustic sensors (5); and - correlating (150) one or more baseline noise indicators and leak noise indicators to de- termine service connections (3) subject to leak indications.

2. The method according to claim 1, wherein the step of correlating the baseline noise indi- cator (51) and the leak noise indicator (52) includes determining a difference between the baseline noise indicator and the leak noise indicator and determining that a service con- nection is subject to a leak indication if the difference is above a predetermined level.

3. The method according to claim 1 or 2, further comprising the step of actively inducing the difference pressure in the utility distribution system or in a part of the utility distribution system, such as by operating a number of pressure controlling devices (4) arranged through-out the pipe network.

4. The method according to claim 3, wherein the sampling rate of the signal from the acoustic sensor is increased during a period of the difference fluid pressure in the utility distribution system or in a part of the utility distribution system.

5. The method according to any of the preceding claims, wherein the pressure measure- ments include system pressure measurements measured as the input pressure delivered

DK 2020 70157 A1 19 at one or more distribution system inlets, such as the pressure provided by one or more supply pumps (4) of the entire distribution network.

6. The method according to any of the preceding claims, wherein the pressure measure- ments include pipe sub-network pressure measurements measured for a sub-set of the pipe network, such as the pressure delivered by a district distribution pump or measured by a district pressure sensor.

7. The method according to any of the preceding claims, wherein the pressure measure- ments include local pressure measurements measured for an individual installation, such as the pressure at a service connection (3) measured by a stand-alone pressure sensor or a pressure sensor integrated in the acoustic sensor or a smart meter including the acoustic sensor.

8. The method according to any of the preceding claims, wherein the acoustic sensors (5) are included in smart utility meters mounted at the service connections.

9. A leak detection system for identifying leak indication in a utility distribution system (1) including a pipe network for supplying a utility to a multitude of service connections (3), the leak detection system comprising: - a plurality of acoustic sensors (5) mounted at the service connections and configured to establish one or more baseline noise indicators and leak noise indicators, - one or more pressure sensing devices (7) for determining the fluid pressure in the pipe network; - a data collection system (8) for collecting pressure data related to the fluid pressure determined by the pressure sensing device and noise data including the one or more base- line noise indicators from the plurality of acoustic sensors; and - a data processing device configured for correlating the one or more baseline noise indi- cators and leak noise indicators to determine service connections subject to leak indica- tions.

10. A leak detection system according to claim 9, further comprising one or more pressure controlling devices arranged for controlling the fluid pressure in the pipe network and configured to induce a difference fluid pressure in the pipe network being higher or lower than a normal fluid pressure of the pipe network.

11. A leak detection system according to claim 10 wherein the one or more pressure control- ling devices is a speed regulated pump (4) in direct or indirect communication with one or more of the acoustic sensors (5) and where the pump reduces the pressure in the pipe network or stops pumping if an indication of leakage has been established.

12. An acoustic sensor (5) or a smart utility meter including the acoustic sensor according to any of the preceding claims, comprising communication means configured to receive com- mands to adjust the noise sampling rate and to transmit a leak noise indicator (52) to a remote location.