WO2023208364A1

WO2023208364A1 - System and method for reliable detection of a leak in a fluid containing structure

Info

Publication number: WO2023208364A1
Application number: PCT/EP2022/061521
Authority: WO
Inventors: Alexey ARBUZOV; John Gaffney; Ilya Mokhov; Neeraj SHAH
Original assignee: Siemens Aktiengesellschaft
Priority date: 2022-04-29
Filing date: 2022-04-29
Publication date: 2023-11-02

Abstract

The invention relates to detection of a leak in a fluid containing structure, e. g. a water, oil, or gas distribution system, especially with focus on high reliability and avoidance of false alarms. The leak detection process applies a standard acoustic leak detection (ALD) method for detection of a leak LK in the fluid containing structure, wherein an execution of the acoustic leak detection (ALD) method depends on fluid properties, especially certain pressures, of a fluid in the fluid containing structure. The fluid properties are processed by a suitable function f to determine a noise measure which represents current noise in the fluid containing structure and the execution of the acoustic leak detection (ALD) method preferably depends on the noise measure determined from the measured fluid properties.

Description

202207051 1 Description System and method for reliable detection of a leak in a fluid containing structure The invention relates to detection of a leak in a fluid con- taining structure, e.g. a water, oil, or gas distribution system, especially with focus on high reliability and avoid- ance of false alarms. Leakage in a fluid containing structure, e.g. a pipeline, a container, or a system of interconnected pipelines, contain- ers, and/or other vessels, might result in a loss of the flu- id. In case the fluid is a harmless substance and the quanti- ty of lost fluid is low, the damage resulting from the loss might remain moderate and essentially limited to the finan- cial value of the lost fluid. However, in case the fluid is hazardous and/or the quantity of lost fluid is substantial, severe damages of the environment of the fluid containing structure are expectable besides the pure financial damage. In any case, an early detection of leakage is of highest in- terest. For example, the fluid containing structure might be a fluid guiding pipeline system guiding a fluid from one or more points A to one or more points B, wherein the fluid might be water, oil, or some other liquid as well as a gas. In one of several imaginable concrete embodiments, the fluid containing structure is a water transmission and distribution network. Such a pipeline system typically comprises a plurality of in- terconnected vessels, e.g. tubes and/or containers. In a less complex embodiment, the fluid containing structure can be a simple tube or duct connecting two points A and B. In general terms, the fluid containing structure is a structure which contains a fluid or which guides a fluid. Leakage in the fluid containing structure might arise due to multiple reasons, for example wear and tear, mechanical in- 202207051 2 terference, pressure spikes, faulty elements, etc. of the vessels of the structure. As indicated above, an early leak- age detection is of high interest, but fluid containing structures are often buried underground and/or are extremely extensive, i.e. large with lengths of several kilometers and complex, so that detection and localization of the leak be- comes a challenging task. One solution to observe a fluid containing structure with re- gard to occurrence of leaks applies the “acoustic leak detec- tion” (ALD) approach, which shall be the method of choice to detect a leak in the solution proposed herein as well. Just for example, an ALD method is disclosed in WO2014014378A1 and in US2022082467. Based on that and on further prior art it can assumed that the ALD method the its way of working is sufficiently well known. The detection via ALD might include the pure determination whether a leak is present or not and optionally the localization of such a leak. ALD utilizes one or more acoustic loggers, e.g. microphones, installed all over the fluid containing structure at suitable locations to record sound in the structure. In principle, ALD is based on differentiating leak sound, caused by the interaction of the fluid with the leak, from the regular sound or “noise” aris- ing during normal operation of the fluid containing struc- ture, e.g. caused by operation of devices of the fluid con- taining structure and/or caused by regular fluid behavior in the vessel, e.g. the fluid flowing through the vessel without abnormal disturbances. Therein, the leak sound is typically based on abnormal disturbances in the fluid in connection with the leak. For example, such abnormal disturbances can be caused by a part of the fluid streaming through the leak. Al- so, sound generating abnormal disturbances in the fluid can arise when the fluid flows along a section of a surface with irregularities due to the leak. However, the determination of leak sound and identification of location of leaks in the fluid containing structure by means of acoustic leak detection ALD is a challenging problem 202207051 3 because the measurable sound is an overlay of the regular sound and potential leak sound so that the ALD approach is typically disturbed by regular noise produced by various net- work elements of the fluid containing structure (in this con- text the regular sound is considered as noise). On the one hand, such noise might be interpreted by an evaluation system to be caused by an alleged leak such that false alarms are initiated. On the other hand, the noise might exceed the acoustic leak sound so that the leak cannot be detected. Both scenarios disturb reliable leakage detection. Therefore, a solution is required which enables detection of a leak in a fluid containing structure with high reliability and minimized risk of false alarms, e.g. due to interference noise of various elements of the fluid containing structure. This is solved by the method suggested in claim 1, by the system as per claim 12, and by the fluid containing structure of claim 16. In the leakage determination process proposed herein with an acoustic leak detection (ALD) method for detection of a po- tential leak LK in a fluid containing structure, an execution of the acoustic leak detection (ALD) method depends on cur- rent fluid properties of a fluid in the fluid containing structure (100) which can be measured in the leakage determi- nation process with respective sensors, e.g. pressure trans- ducers. Here and in the following, expressions like “execution of the acoustic leak detection method depends on current fluid prop- erties” or on other parameters means that a decision whether or not the acoustic leak detection method is executed depends on those fluid properties or other parameters, as the case may be. Thus, the leakage determination process comprises a first step of determining current fluid properties and, de- pending on the outcome of the first step, a second step of executing the ALD method. 202207051 4 For example, the process can be applied very efficiently nearby a pressure reducing valve (PRV’) arranged in the fluid containing structure which has strong impact on noise in the structure. In that case, the fluid properties comprise a pressure p_u(102’) in the fluid upstream and a pressure p_d(102’) in the fluid downstream of the pressure reducing valve (PRV’). However, the measured current fluid properties can be pro- cessed with a predefined function f_102’ to determine a noise measure NOI_201’(ENV(102’))=f_102’(p_u(102’), p_d(102’)), which rep- resents current noise SND_201’(ENV(102’)) in the fluid contain- ing structure (100) at a location of a particular acoustic logger 201’ applied by the acoustic leak detection (ALD) method. The predefined function f_102’ expresses a preferably unambiguous relationship between the measured fluid proper- ties p_u(102’), p_d(102’) and the corresponding noise measure NOI_201’(ENV(102’)). The execution of the acoustic leak detec- tion (ALD) method depends on the determined noise measure NOI_201’(ENV(102’)). More concrete, the acoustic leak detection (ALD) method is executed only in case the current noise meas- ure NOI_201’(ENV(102’)) fulfills a predefined condition COND(102’), e.g. in case the noise measure NOI_201’(ENV(102’)) is below a threshold THRES(102’). Therein, the function f_102’ is established in a preparation phase PHP of the leakage determination process by, in a first step, continuously measuring over time t, e.g. for several days, the fluid properties p_u,PHP(102’)(t), p_d,PHP(102’)(t) and measuring, at the same time, concrete noise data SND_201’,PHP(ENV(102’))(t) in the fluid containing structure and, in a second step, assigning or correlating with each other, respectively, the noise data SND_201’,PHP(ENV(102’))(ti) measured at certain points ti in time t to fluid properties p_u,PHP(102’)(ti), p_d,PHP(102’)(ti) measured at the same points ti in time. The latter creates the relationship f between the fluid properties and the corresponding noise data. In other words, for all or at least most t, a noise 202207051 5 SND_201’,PHP(ENV(PRV’))(t1) measured at a point t1 in time is assigned to a fluid properties (p_u,PHP(102’)(t1), p_d,PHP(102’)(t1)) measured at the same point t1 in time. Here and in the following, an expression “at the same point in time” or similar is to be understood such that it can cover a time window of e.g. minutes, i.e. the “point” in time can ac- tually be a time span. Thus, the function f_102’ is established to provide, upon receiving fluid properties (p_u(102’), p_d(102’)) as an input, those noise data SND_201’,PHP(ENV(102’)(tx) as an output NOI_201’(ENV(102’)) which have been assigned to measured fluid properties (p_u,PHP(102’)(tx), p_d,PHP(102’)(tx)) which are best matching with the input fluid properties (p_u(102’), p_d(102’)). The leakage determination process can be applied and executed separately for each one of NENV≥1 certain limited environ- ments ENV(102’) of correspondingly NDEV≥1 particular poten- tially noise causing devices of the fluid containing struc- ture. Thus, the fluid containing structure is divided into one or more environments, wherein, in case of NENV=1, i.e. only one environment, the one environment can be the whole fluid containing structure. Typically, NDEV=NENV is applica- ble, i.e. one particular environment ENV(102’) is assigned to one particular device or, in other words, one particular de- vice is characterized by one particular environment ENV(102’). For each environment ENV(102’) and/or device, the noise meas- ure NOI_201’(ENV(102’))=f_102’(p_u(102’), p_d(102’)) represents cur- rent noise SND_201’(ENV(102’)) in the limited environment ENV(102’) of a particular potentially noise causing device of the fluid containing structure (100). The limited environment ENV of a device is that area in the fluid containing struc- ture in which maximum noise caused by the device would be disturbing potential acoustic leak detection measurements so that the results of those ALD measurements are significantly less reliable, e.g. due to an unacceptable high ratio of false alarms. Typically but not necessarily, a fluid contain- 202207051 6 ing structure comprises a plurality of potentially noise causing devices and, correspondingly, a plurality of environ- ments. Therein, for each particular device, the current fluid prop- erties p_u(102’), p_d(102’) are measured in a limited surround- ing SURR(102) of the particular potentially noise causing de- vice of the fluid containing structure, preferably both up- stream and downstream of the particular device. The limited surrounding SURR(102’) is that area in the fluid within the fluid containing structure and typically within the environ- ment ENV(102’) in which changes of an operating state of the device have a significant, measurable influence on the fluid properties, both upstream and downstream of the device. For example, in case the device is a pressure reducing valve (PRV) and the fluid properties are pressures in the fluid, the surrounding would extend one or several ten meters both upstream and downstream of the device because in that area pressures in the fluid would be influenced by the operating state of the PRV, e.g. “open” or “closed”. Preferably, at least one fluid property measurement happens upstream of the device and at least one fluid property measurement happens downstream, so that, for example, upstream and downstream pressures are determined. Moreover, for each environment ENV(102’), the leakage deter- mination process LDM(102’) includes a step LDM1(102’) in which the current fluid properties (p_u(102’), p_d(102’)) in the surrounding SURR(102’) of the particular device are meas- ured, a step LDM2(102’) in which the measured current fluid properties (p_u(102’), p_d(102’)) are processed to determine the current noise measure NOI_201’(ENV(102’)) by applying the function f_102’ with NOI_201’(ENV(102’))=f_102’(p_u(102’), p_d(102’)), a step LDM3(102’) in which the determined current noise meas- ure NOI_201’(ENV(102’)) is evaluated to decide whether a prede- fined condition COND(102’) is fulfilled, and a step LDM4(102’) in which the acoustic leak detection (ALD) method is executed for the environment ENV(102’) of the particular 202207051 7 device in case the predefined condition COND(102’) is ful- filled. Moreover, for each particular device, the function f_102’ is established for the particular device and/or for its corre- sponding environment ENV(102’) in a preparation phase PHP of the leakage determination process by, in a first step, con- tinuously measuring over time t, e.g. for several days, the fluid properties p_u,PHP(102’)(t), p_d,PHP(102’)(t) in the sur- rounding SURR(102’) of the particular device and measuring, at the same time, noise data (SND_201’,PHP(ENV(102’))(t)) in the environment ENV(102’) of the particular device (102’), which might sometimes be dominated by noise caused by the device (102’), and, in a second step, assigning or correlating with each other, respectively, the noise data SND_201’,PHP(ENV(102’))(ti) measured at certain points ti in time t to a constellation CON(p_u,PHP(102’)(ti), p_d,PHP(102’)(ti)) of fluid properties p_u,PHP(102’)(ti), p_d,PHP(102’)(ti) measured at the same points ti in time. This creates the relationship between the fluid properties and the corresponding noise measure: A noise SND_201’,PHP(ENV(PRV’))(t1) measured in the preparation phase PHP at a point t1 in time is assigned to a constellation CON of fluid properties (p_u,PHP(102’)(t1), p_d,PHP(102’)(t1)) measured at the same point t1 in time. Just for example, a constellation CON of fluid properties can be a difference or a ratio of those fluid properties. Further approaches to form constellations are de- scribed below. With that, the function f_102’ is established to provide, upon receiving fluid properties p_u(102’), p_d(102’) as an input, those noise data SND_201’,PHP(ENV(102’)(tx) as an output NOI_201’(ENV(102’)) which have been assigned to the particular constellation CON(p_u,PHP(102’)(tx), p_d,PHP(102’)(tx)) of meas- ured fluid properties p_u,PHP(102’)(tx), p_d,PHP(102’)(tx) which matches best with the respective constellation CON(p_u(102’), p_d(102’)) of input fluid properties p_u(102’), p_d(102’). 202207051 8 Therein, for a particular environment ENV(102’), the acoustic leak detection (ALD) method applies, if executed, at least one acoustic logger located in the particular environment ENV(102’) to measure noise in the fluid in environment ENV(102’) for leakage detection, wherein the same at least one acoustic logger is applied in the preparation phase PHP to measure the noise data (SND_201’,PHP(ENV(102’))(t)). The acoustic leak detection (ALD) method is executed in the particular environment ENV(102’) in case the noise measure NOI_201’(ENV(102’)) fulfills a predefined condition COND(102’). The predefined condition COND(102’) is defined such that a fulfillment of the predefined condition COND(102’) is achieved in case current noise SND(100) in the environment ENV(102’), as represented by the noise measure, does not sig- nificantly disturb the acoustic leak detection (ALD) method and, vice versa, fulfillment is not achieved in case the noise SND(100) in the environment ENV(102’), as represented by the noise measure, is such that it would significantly disturb the acoustic leak detection (ALD) method, so that the outcome of the ALD method would not be sufficiently reliable. For example, a threshold value THRES(102’) can be introduced and the noise measure NOI_201’(ENV(102’)) can be related to the threshold. Then, only in case NOI_201’(ENV(102’))<THRES(102’) the condition might be fulfilled. As already indicated, in a preferred embodiment the particu- lar device is a pressure reducing valve (PRV’) arranged in the fluid containing structure (100) and the fluid properties p_u(102’), p_d(102’) comprise a pressure p_u(102’) in the fluid upstream and a pressure p_d(102’) in the fluid downstream of the particular pressure reducing valve (PRV’). A corresponding leakage determination system for detection of a leak LK in a fluid containing structure with one or more potentially noise causing devices, i.e. the devices belong to the structure, but not to the system, is configured to exe- cute the process described above so that the execution of the 202207051 9 acoustic leak detection (ALD) method is depending on current fluid properties p_u(102’), p_d(102’) of the fluid in the fluid containing structure. The system might comprise one or more particular sensors as- signed to a particular potentially noise causing device of the fluid containing structure for measuring the fluid prop- erties p_u(102’), p_d(102’), wherein the sensors are arranged in the fluid containing structure in a limited surrounding SURR(102’) of the particular device as defined above. Therein, at least one of the particular sensors is arranged upstream of the particular device and at least one more of the particular sensors is arranged downstream of the particu- lar device. The particular device can be a pressure reducing valve (PRV’) arranged in the fluid containing structure and the particular sensors assigned to the particular device can be pressure transducers for measuring pressures p_u(102’), p_d(102’) in the fluid, wherein the fluid properties p_u(102’), p_d(102’) com- prise a pressure p_u(102’) in the fluid upstream and a pres- sure p_d(102’) in the fluid downstream of the particular pres- sure reducing valve (PRV’). Consequently, a fluid containing structure in line with the solution proposed herein comprises a leakage determination system as described above. The fluid containing structure can be a network for providing the fluid from one or more sources to one or more consumers, wherein the fluid can be water or oil or gas. It is to be understood that the elements and features recited in the appended claims may be combined in different ways to produce new claims that likewise fall within the scope of the present invention. Thus, whereas the dependent claims append- ed below depend from specific independent or dependent 202207051 10 claims, it is to be understood that these dependent claims can, alternatively, be made to depend in the alternative from any preceding or following claim, whether independent or de- pendent, and that such new combinations are to be understood as forming a part of the present specification. DESCRIPTION OF THE FIGURES In the following, possible embodiments of the different as- pects of the present invention are described in more detail with reference to the enclosed figures. The objects as well as further advantages of the present embodiments will become more apparent and readily appreciated from the following de- scription of the preferred embodiments, taken in conjunction with the accompanying figure in which: FIG 1 shows a fluid containing structure; FIG 2 shows a flow chart of the leakage determination method. DETAILED DESCRIPTION FIG 1 is a simplified and reduced visualization of a fluid containing structure 100 with one or more vessels 101 for containing a fluid 110 and/or for guiding the fluid 110 from one or more points A, e.g. sources of the fluid, to one or more points B, e.g. consumers. In reality, the structure 100 can be much more complex. The arrows in the vessels indicated the direction of flow of the fluid from an upstream direction to a downstream direction. The vessels 101 can be, for example, pipes, tubes, or passag- es 101p, containers or reservoirs 101c, and/or further typi- cal and/or imaginable structures 101x which might be required to fulfill the purpose of the fluid containing structure 100. However, such pipes, containers, and structures etc. will be subsumed in the following under the term “vessels” 101. Some 202207051 11 of those vessels 101 can be interconnected at respective crossings. Moreover, the fluid containing structure 100 comprises one or more types of active devices 102, e.g. valves 102v, pumps 102p, and/or further typical and/or imaginable elements 102x which might be required to fulfill the purpose of the fluid containing structure 100. However, such valves 102v, pumps 102p, and/or elements 102x will be subsumed in the following under the term “devices” 102. The devices 102 can be used to manipulate a flow of the fluid 110. Control of the devices 102 is performed by a control system 120 of the fluid containing structure 100. The control system 120, which can be a computer implemented system with a pro- cessor executing a respective software, is configured to con- trol the devices 102 based on input data. The input data pro- cessed by the control system 120 can be data from an operator of the fluid containing structure 100 and/or data from sen- sors 103 positioned in the fluid containing structure 100 at positions of interest or relevance, e.g. along the vessels 101 and devices 102, e.g. positioned at critical crossings, important devices 102, and/or further positions of interest or relevance. Typically, but not necessarily, each device 102 would be equipped with a respective sensor 103 which provides relevant operational data of the assigned device 102. Therewith, the typical fluid containing structure 100 com- prises a control system 120, one or more vessels 101, one or more devices 102, and/or sensors 103. In practice, the con- crete setup and architecture of a particular fluid containing structure 100 depends on the purpose and field of use of the structure 100. Thus, in an exemplary minimal realization of the fluid con- taining structure 100 still underlying the present invention, the structure 100 merely has to contain and hold the fluid 110, i.e. it indeed just operates as a container. In that 202207051 12 case, the structure 100 might only comprise one container vessel 101, but no further vessels. A slightly enhanced real- ization of this minimal realization might additionally com- prise a valve 102 for releasing the fluid from the container vessel 101 and/or for letting additional fluid 110 into the container vessel 101. In that case, a control system 120 for controlling the valve 102 might be foreseen or the valve 102 might be operated manually. In a more complex realization of the fluid containing struc- ture 100 still underlying the present invention, the struc- ture 100 comprises a plurality of vessels 101, a plurality of devices 102, a plurality of sensors 103, and a control system 120. Exemplarily, but not limiting the invention, such a com- plex fluid containing structure 100 can be embodied as a wa- ter guiding pipeline system (WGPS) 100. The WGPS 100 can be used to systematically guide the fluid 110, in this case wa- ter 110, from sources A to consumers B via the vessels 101, with the help of the devices 102, and controlled by the con- trol system 120. Of course, a similar structure 100 can be used to guide other fluids like oil or gas etc. from A to B. In any realization of the fluid containing structure 100, oc- currence of a leak LK might result in the damages and risks indicated above. Therefore, an early detection of leakage is of highest interest. Therein, “detection” might mean the pure determination whether a leak is present or not and optionally the localization of such a leak. For that reason, the fluid containing structure 100 is equipped with a leakage determination system 200 which is em- bodied and configured to apply the acoustic leak detection approach ALD. The ALD approach typically foresees to acousti- cally measure sound SND in the fluid containing structure 100 with the help of one or more acoustic loggers 201, e.g. em- bodied as corresponding microphones, and to analyze the meas- ured sound SND, e.g. its volume, i.e. the loudness, to iden- tify potential contributions to the sound SND caused by a 202207051 13 presumable leak LK. Alternatively or additionally, the spec- trum of the measured sound SND might be a basis for further analysis to detect leakage. However, an approach only based on volume is a simplification, but it yields acceptable re- sults for many cases. In general terms, a representation r(SND) of the sound SND is measured, wherein the representa- tion r(SND) might be, for example, the volume and/or the spectrum of the sound. In the scenario described herein, it is not of highest relevance which one or more of the sound properties are analyzed and it can be assumed, for the sake of simplicity, that the analysis described below is based on sound volume vol(SND), i.e. r(SND)=vol(SND). The leakage determination system 200 comprises one or more acoustic loggers 201 installed throughout the fluid contain- ing structure 100 at suitable locations as well as an evalua- tion system 220. The evaluation system 220, which can be a computer implemented system with a processor executing a re- spective software, can be an independent system or it can be implemented in the control system 120, if available. Each in- stalled acoustic logger 201 acoustically measures sound SND, e.g. the respective volume, in the fluid containing structure 100 and provides the respective representation r(SND), e.g. at regular intervals and/or initiated by the evaluation sys- tem 220. The measurements can be sensitive for sound SND oc- curring both in the structure 100 itself, i.e. in the walls of the vessels 101 etc., and occurring in the fluid 110. For example, some acoustic loggers 201 might be arranged and con- figured such that they essentially measure sound in the fluid 110 while other acoustic loggers 201 are arranged and config- ured such that they essentially measure sound in the struc- ture 100 itself. Alternatively or additionally, some or all acoustic loggers 201 can be arranged and configured such that they measure sound both in the structure 100 itself and in the fluid 110. In any case, the loggers 201 act as acoustic sensors for sound SND in the fluid containing structure 100 and the respective sensor measurement data, i.e. the repre- sentation r(SND) of the sound SND, are transferred to the 202207051 14 evaluation system 220 for further processing for leakage de- termination. The processing and analysis of the measurement data r(SND) of the acoustic loggers 201 in the evaluation system 220 might result in the insight that the fluid containing structure 100 comprises a leak LK, e.g. in case the sound SND measured by one or more loggers 201’ shows suspicious volume or spectrum etc. in r(SND). In that case, the leakage determination sys- tem 200 is configured to initiate an alarm status which might, for example, notify an operator of the fluid contain- ing structure 100 of the potentially critical situation and/or which might result in initialization of automatic measures like closing valves, stopping pumps, and/or shutting down the overall system. As night is usually a sufficiently quiet period with lowest regular sound SND(100) in the structure 100, typical acoustic measurements with acquisition of measurement data r(SND) take place at night in order to avoid unwanted disturbances, i.e. noises not related to leaks, so that potential leak sound SND(LK) can be distinguished from regular sound SND(100) more easily. Nevertheless, unambiguous identification of the pres- ence of a leak LK with low risk of false alarms during the processing and analysis of the measurement data r(SND) of the acoustic loggers 201 in the evaluation system 220 is chal- lenging and/or might even involve relatively high manual ef- forts because, as indicated above, the overall sound SND and r(SND) measurable by the acoustic loggers 201 is an overlay of potential leak sound SND(LK) caused by a leak LK with the regular sound SND(100) of the fluid containing structure 100. Thus, the leakage determination system 200 has to be able to identify leak sound SND(LK) despite the presence of regular, unavoidable sound and noise SND(100), respectively. In the following, the expression “regular, unavoidable sound and noise SND(x), respectively,” will occasionally be replaced by “noise SND(x)” or “regular sound SND(x)” for the sake of brevity. 202207051 15 The noise SND(100) can be caused by different sources. For example, the devices 102 of the structure 100 can be sources of acoustic noise SND(102) contributing to the noise SND(100), i.e. the noise SND(100) is essentially an overlay of the regular sounds SND(102) generated by those devices 102 during operation of the structure 100. One concrete example for a regular acoustic noise SND(102) causing device 102 which is typically present in a fluid containing structure 100 might be a pump which operates at a certain frequency and which generates corresponding noise SND(102). Another con- crete example for a regular noise noise SND(102) causing de- vice 102 might be a pressure reducing valve (PRV) which is often used to reduce an operating pressure at suitable loca- tions in the fluid containing structure 100. In certain oper- ating regimes, the flow of fluid 110 through a PRV might pro- duce an acoustic noise SND(PRV) with properties similar to the noise SND(LK) caused by a leak LK. The fluid flow and the respective noise properties, e.g. volume and spectrum, depend on the specific design of the PRV and on the inflow and out- flow pressures or, in the following, upstream pressures p_u and downstream pressures p_d, in each case from the perspec- tive of the particular PRV. For example, the downstream pres- sure p_d might be given by a setpoint or desired pressure p_d on the downstream side. A major part of noise SND(PRV) that can be caused by a PRV can be generated by cavitation which occurs in case the PRV operates in a non-optimal state. Therein, a non-optimal state is typically unavoidable during normal operation, since upstream and downstream pressures p_u, p_d are subject to fluctuations, e.g. due to consumption, pumping operations, and elevation of certain pipe sections of the network etc. Consequently, the noise SND(PRV) generated by the PRV fluctuates as well. However, in case the leakage determination system 200 has in- itiated the alarm status, a subsequent field inspection is performed. During the field inspection, an expert assesses essentially manually whether a regular noise causing device 202207051 16 102, e.g. a PRV, is topologically in the vicinity of that acoustic logger 201’ that caused the alarm status. In case such PRV is near the logger 201’ and a measured sound r(SND) is proven to be dominated by noise SND(PRV) caused by the PRV, the alarm might be classified as a false alarm and the alarm status can be reset. In specific cases additional in- vestigations might be required to identify whether the alarm status is based on a false alarm and suitable network opera- tions have to be executed. Such network operations typically require closing of the PRV under investigation to stop the flow through the PRV, which might result in isolating some consumers downstream of the PRV. In case the PRV is the source of the noise, such an experiment allows to stop the cavitation noise and to confirm that the noise was coming from the PRV. An alternative approach is to perform the sound measurements in close proximity to the location of the PRV to be able to unambiguously distinguish whether sound is gener- ated by the PRV or not. Thus, the unambiguous, reliable identification of the pres- ence of a leak LK with low risk of false alarms during the processing and analysis of the measurement data r(SND) of the acoustic loggers 201 in the evaluation system 220 is there- fore challenging and/or effortful due to the presence of reg- ular noise SND(100) generated during normal operation of the fluid containing structure 100 which can hinder the identifi- cation of sound SND(LK) caused by a leak LK. The solution for reliable leakage detection proposed herein is based on the approach to detect situations, e.g. in the form of time windows dT, in which the noise SND(100) present at a location of an acoustic logger 201 is low enough to ena- ble the reliable identification of sound SND(LK) in the fluid containing structure 100 caused by a leak LK. For that, the solution applies measurements of current fluid parameters which allow conclusions w.r.t. noises SND(102) currently caused potentially by the devices 102. In case a noise meas- ure NOI₂₀₁(ENV(102)), being a measure for noise SND measured 202207051 17 with a particular acoustic logger 201 in an environment ENV(102) of a particular device 102, fulfills certain condi- tions, e.g. being above or below a given threshold, leakage detection is performed. Therein, the range and extension of the “environment” ENV(102’) of a particular device 102’ de- pends on technical details and properties of the device 102’, on the setup of a section of the fluid containing structure 100 in which the particular device 102’ is located, and po- tentially on further properties. In general, the extension of the environment ENV(102) of a device 102 can take into ac- count how far noise SND(102) caused by device 102 might have significantly disturbing influence on leakage detection meas- urements in the fluid containing structure 100. For example, such environment might extend up to several hundred meters both upstream and downstream of the respective particular de- vice 102. A noise measure NOI₂₀₁(ENV(102)) might be the volume, the spectrum, or some other property of the real noise SND₂₀₁(ENV(102)) at the location of the acoustic logger 201 in the environment ENV(102) or it might be composed of other pa- rameters which allow a reliable conclusion on the noise SND₂₀₁(ENV(102)). For example, in the below explanations cer- tain pressure conditions in the fluid in the surrounding SURR(102) of the device 102 will be used to compose the noise measure NOI₂₀₁(ENV(102)). For the sake of clarity, it might be mentioned that the noise SND₂₀₁(ENV(102)) and therewith the noise measure NOI₂₀₁(ENV(102)) does not necessarily only rep- resent noise SND(102) caused by the device 102, but it can also include components of other noises, e.g. general back- ground noise SND(100) in the structure 100. Thus, the noise SND₂₀₁(ENV(102)) measurable in the environment ENV(102) of the device 102 is typically an overlay of such general background noise and of noise caused by the particular device 102. The solution is based on the assumption that generation of noise SND(102’) by a particular regular noise causing device 102’ of the structure 100 is related to fluid properties in 202207051 18 the surrounding SURR(102’) of that particular regular noise causing device 102’, i.e. upstream and/or downstream and top- ologically in the vicinity of the particular regular noise causing device 102’, e.g. within a range of one or several ten meters, both upstream and downstream. Thus, insights about current fluid properties in the surrounding SURR(102’) of the particular regular noise causing device 102’, e.g. provided by suitable sensors 202 of the leakage determination system 200 arranged in the surrounding SURR(102’), can pro- vide the noise measure NOI_201’(ENV(102’)) representing noise measurable by particular acoustic logger 201’ in the environ- ment ENV(102’) of device 102’ and, therewith, allow conclu- sions about current presence of noise SND(102’) generated by the particular device 102’. In the consequence, resulting in- sights about current noise SND(102’), expressed by NOI_201’(ENV(102’)) at the location of a particular acoustic logger 201’ in the environment ENV(102’), can be used to de- cide whether a measurement of sound SND with that acoustic loggers 201’ in the environment ENV(102’) of the particular potentially noise causing device 102’ is promising: For exam- ple, in case the volume of such current noise SND_201’(ENV(102’)) derived from the measurements of the fluid properties in the surrounding SURR(102’) is below a given threshold, a measurement of sound SND for leakage detection with the particular one or more acoustic loggers 201’ in the environment ENV(102’) of the particular device 102’ would be promising since it can be assumed that the measurement of sound SND with the acoustic loggers 201’ in the environment ENV(102’) is not significantly disturbed by current noise SND(102’) of the device 102’. In contrast, in case the volume of such current noise SND_201’(ENV(102’)) in the environment ENV(102’) exceeds the given threshold, it might be advisable to waive sound measurements with the acoustic loggers 201’ in the environment ENV(102’) or, alternatively, an evaluation of potential measurement data provided by those loggers 201’ is either not performed or evaluation results are not further considered or consideration of such evaluation results is made with reservation etc. In other words, leakage detection 202207051 19 in an environment ENV(102’) of a particular device 102’ is only performed in case a representation of noise SND_201’(ENV(102’)), potentially generated by the particular device 102’, i.e. the noise measure NOI_201’(ENV(102’)), ful- fills predefined conditions, e.g. in case the noise measure NOI_201’(ENV(102’)) does not exceed a predefined threshold. For the sake of clarity, the expression “leakage detection” might mean in this context the data acquisition with noise loggers 201’ itself or, in case data acquisition is anyway performed, the processing of the results of the data acquisition or, in case such processing is anyway performed, the consideration of the respective processing results in the leakage determi- nation system 200, i.e. the processing results might simply be dismissed. Thus, the solution allows to identify opportunities for reli- able leakage detection measurements, e.g. via a regular ALD approach. This results in a reduction of false alarms, i.e. recordings triggered by noise not related to leaks. In a concrete exemplary embodiment of this solution to iden- tify promising opportunities for measurement of sound for leakage detection, a particular potentially noise causing de- vice 102’ and its environment ENV(102’) are considered. Fur- thermore, the example assumes that the particular device 102’ is a particular pressure reducing valve PRV’. The generation of noise SND(PRV’) by the particular PRV’ is related to pressures p_u upstream and pressures p_d downstream of that particular PRV’ in its surrounding SURR(PRV’) as in- troduced above. Thus, the “fluid properties”, from which a noise measure NOI_201’(ENV(PRV’)) for the noise and regular sound SND(PRV’) potentially caused by the particular PRV’ can be derived, are, in this exemplary case, represented by the fluid pressures p_u, p_d upstream and downstream of the partic- ular PRV’. Correspondingly, the respective sensors 202’ of the leakage determination system 200 for determining the up- stream and downstream fluid pressures p_u, p_d are pressure 202207051 20 transducers 202’, arranged in the surrounding SURR(PRV’) up- stream and downstream of the PRV’. Thus, information about current pressures p_u upstream and current pressures p_d downstream of the particular PRV’ is utilized to identify opportunities in time where a disturb- ance of sound measurements due to noise SND(PRV’) generated by the particular PRV’ on the acoustic loggers 201’ in the environment ENV(PRV’) of the particular PRV’ is minimized. The corresponding knowledge about minimum acoustic disturb- ance by the particular PRV’ is used to perform leakage detec- tion based on sound measurements with the acoustic loggers 201’ in the environment ENV(PRV’) of the particular PRV’ while knowledge about high acoustic disturbance based on sound of the PRV’ results in a waiver. In one concrete exemplary embodiment, sound measurements with the one or more acoustic loggers 201’ to determine r_201’(SND) for leakage detection with ALD are performed only in case the measure NOI_201’(ENV(PRV’)) of current noise SND at the loca- tion of the particular acoustic logger 201’, potentially dom- inated by the particular PRV’, remains below a threshold THRES, i.e. as long as NOI(PRV’)<THRES. The noise measure NOI_201’(ENV(PRV’)) shall be derived from the current pressures p_u, p_d upstream and downstream of the particular PRV’. Thus, a determination of those pressures p_u, p_d with the pressure transducers 202’ allows to assess whether the measurements of sound with the acoustic loggers 201’ would be promising, i.e. sufficiently undisturbed by noise SND(PRV’), and whether it should be performed. For that purpose, the pressure transducers 202_u’, 202_d’ are installed upstream and downstream of the particular PRV’ in its surrounding SURR(PRV’) in suitable distance to the PRV’ for measuring respective current pressures p_u(PRV’), p_d(PRV’). The current pressures p_u(PRV’), p_d(PRV’) are trans- ferred to the evaluation system 220 of the leakage determina- tion system 200 for further consideration, wherein the evalu- 202207051 21 ation system 220 is configured to process the current pres- sures p_u(PRV’), p_d(PRV’) to determine the noise measure NOI_201’(ENV(PRV’)) as explained below. The determination of the noise measure NOI_201’(ENV(PRV’)) from measured current pressures p_u(PRV’), p_d(PRV’) might apply different approaches. For example, a difference p_u(PRV’)- p_d(PRV’) and/or a ratio p_u(PRV’)/p_d(PRV’) might qualify to provide suitable noise measures NOI_201’(ENV(PRV’)) or a combi- nation of both or other operations from which a reliable con- clusion NOI_201’(ENV(PRV’)) w.r.t. the noise SND(PRV’) current- ly generated by the particular PRV’ is possible. In general terms, the noise measure NOI_201’(ENV(PRV’)) is a function of current pressures p_u(PRV’), p_d(PRV’), i.e. NOI_201’(ENV(PRV’))=f(p_u(PRV’), p_d(PRV’)). In general terms, the leakage determination method LDM to be explained in the following and sketched in FIG 2, typically executed during regular operation PHOP of the fluid contain- ing structure 100, first checks, based on determination of the noise measure NOI, whether leakage detection is promis- ing. If so, leakage detection is executed, preferably based on an ALD method. If not, i.e. in case noise in the structure 100 is too disturbing, leakage detection is not executed. However, as indicated above the noise measures NOI_201’(ENV(PRV’)) or, more general, NOI_201’(ENV(102’)) depend on the particular device 102’ under consideration: It is ex- pectable that for a certain point t1 in time the noise meas- ure NOI_201’(ENV(102’))(t1) of a first device 102’ is low and harmless, while the noise measure NOI_201’(ENV(102”))(t1) for another device 102” at the same point t1 in time is high and disturbing. In that scenario, leakage detection should be performed with the acoustic logger 201’ in the environment ENV(102’) and for device 102’, but not with an acoustic log- ger 201” in the environment ENV(102”) and for device 102”. Therefore, the leakage determination method LDM=LDM(102’) ex- plained below refers to a particular device 102’ of the fluid containing structure 100 and its environment ENV(102’) and 202207051 22 not to the overall structure 100. Consequently, the leakage determination method LDM(102’) might be executed separately for different devices 102. Again using the example of a particular pressure reducing valve PRV’, the leakage determination method LDM(PRV’) for the environment ENV(PRV’) of particular PRV’ comprises a step LDM1(PRV’) of measuring the current upstream and downstream pressures p_u(PRV’), p_d(PRV’) with the respective pressure transducers 202_u’, 202_d’ installed upstream and downstream of the particular PRV’ in its surrounding SURR(PRV’). The measured current pressures p_u(PRV’), p_d(PRV’) are trans- ferred to the evaluation system 220, which subsequently pro- cesses the current pressures p_u(PRV’), p_d(PRV’) in a step LDM2(PRV’) of the method LDM(PRV’) to determine the current noise measure NOI_201’(ENV(PRV’)) by applying a predefined function f_PRV’ with NOI_201’(ENV(PRV’))=f_PRV’(p_u(PRV’), p_d(PRV’)) established in a preparation phase PHP as outlined below. In a step LDM3(PRV’), the determined current noise measure NOI_201’(ENV(PRV’)) is further processed and evaluated, respec- tively, in the evaluation system 220 to decide whether leak- age detection itself should be reasonably performed with the particular noise logger 201’ in the environment ENV(PRV’) of the particular PRV’. Therein, the evaluation system 220 checks whether the determined current noise measure NOI_201’(ENV(PRV’)) fulfills one or more predefined conditions COND(PRV’). For example, the evaluation system 220 checks the relationship between the current noise measure NOI_201’(ENV(PRV’)) and a predefined threshold THRES(PRV’) wherein a predefined condition might demand that the current noise measure NOI_201’(ENV(PRV’)) is below the predefined threshold THRES(PRV’). In case the current noise measure NOI_201’(ENV(PRV’)) indeed fulfills the one or more predefined conditions COND, e.g. NOI_201’(ENV(PRV’))<THRES(PRV’), the evaluation system 220 generates a corresponding positive trigger signal TRIG(PRV’). Consequently, the threshold 202207051 23 THRES(PRV’) is preselected and predefined such that it can be assumed that noise SND(PRV’) caused by the particular PRV’ and represented by the noise measure NOI_201’(ENV(PRV’)) does not disturb the leakage detection itself in case NOI_201’(ENV(PRV’))<THRES(PRV’) is applicable. However, in case the predefined condition COND(PRV’) is not fulfilled, the trigger signal TRIG(PRV’) might be negative or zero. In a step LDM4(PRV’), an acoustic leak detection ALD(PRV’) method is indeed executed by the evaluation system 220 with the one or more of the noise loggers 201’ in the environment ENV(PRV’) of the particular PRV’ in case the evaluation sys- tem 220 has generated a positive trigger signal TRIG(PRV’) in step LDM3(PRV’). The acoustic leak detection ALD(PRV’) method applied in step LDM4(PRV’) can be a known ALD method, i.e. the specific ALD method itself is not a core aspect of the invention, resulting in the final assessment whether a leak LK is present. For the sake of clarity, it might be mentioned that the ful- fillment of the one or more conditions COND(PRV’) by the cur- rent noise measure NOI_201’(ENV(PRV’)) of the particular PRV’ is only relevant for executing the ALD method in step LDM4(PRV’) with the particular noise loggers 201’ in the en- vironment ENV(PRV’) of the particular PRV’. Noise loggers 201 not located in the environment ENV(PRV’) are not concerned. For example, other particular noise loggers 201” as well as other pressure transducers 202” for measuring p_u(102”), p_d(102”) might be installed in the environment ENV(102”) of another particular device 102”, e.g. another particular PRV”. A leakage determination method LDM(102”) as described above would be executed separately for that particular device 102” and the evaluation result in step LDM3(102”) would only be applicable for noise loggers 201” in the environment ENV(102”) of the particular device 102”. However, the decision in step LDM3(PRV’) whether leakage de- tection itself with an ALD method should be performed with 202207051 24 the particular noise logger 201’ in the environment ENV(PRV’) depends on the current noise measure NOI_201’(ENV(PRV’)). The current noise measure NOI_201’(ENV(PRV’)) is determined in step LDM2(PRV’) using the predefined function f_PRV’(p_u(PRV’), p_d(PRV’)). The function f_PRV’ is established in a preparation phase PHP for setting up the leakage determination system 200. During the preparation phase PHP, which might last sev- eral days, pressures p_u,PHP(PRV’)(t), p_d,PHP(PRV’)(t) are meas- ured with the pressure transducers 202’ in the surrounding SURR(PRV’) of a particular PRV’, preferably continuously in time t. In parallel and at the same time, the acoustic logger 201’ in the environment ENV(PRV’) measures sound and noise data SND_201’,PHP(ENV(PRV’))(t), respectively, which might be dominated by sound SND(PRV’)(t) caused by the nearby PRV’. Due to the parallel measurements of pressures p_u,PHP(PRV’)(t), p_d,PHP(PRV’)(t) and noise data SND_201’,PHP(ENV(PRV’))(t), the noise data SND_201’,PHP(ENV(PRV’))(t) can be assigned to or cor- related with certain constellations CON(p_u,PHP(PRV’)(t), p_d,PHP(PRV’)(t)) of the measured pressure values p_u,PHP(PRV’)(t), p_d(PRV’)(t). Here and in the following, different approaches to form a re- spective “constellation” CON in the preparation phase PHP are imaginable. For example, the constellations CON(t) of pres- sure values p_u(PRV’)(t), p_d(PRV’)(t) can be differences CON(t)=p_u(PRV’)(t)-p_d(PRV’)(t), ratios CON(t)=p_u(PRV’)(t)/p_d(PRV’)(t), or other mathematical opera- tions which use both p_u(PRV’)(t) and p_d(PRV’)(t) as an input IN(t) and produce an output OUT(t) depending on p_u(PRV’)(t) and p_d(PRV’)(t). This shall include an embodiment in which the measured values of p_u(PRV’)(t) and p_d(PRV’)(t) are simply collected to form a value pair {p_u(PRV’)(t), p_d(PRV’)(t)} without further processing. It should be noted that the approach to form a constellation of pressure values during regular operation PHOP as explained below and the approach to form a constellation in the prepa- ration phase PHP should be identical. For example, in case 202207051 25 constellations are formed in the preparation phase PHP based on differences CON_PHP(t)=p_u,PHP(PRV’)(t)-p_d,PHP(PRV’)(t), a con- stellation CON in the operation phase PHOP and in the leakage determination method LDM, respectively, should also be formed based on a difference of measured pressures, i.e. CON_PHOP=p_u(PRV’)-p_d(PRV’). This assignment or correlation, respectively, of constella- tions CON_PHP(t) on the one side and noise data SND_201’,PHP(ENV(PRV’))(t) on the other side for all or at least many t determined in the preparation phase PHP allows to con- clude during regular operation PHOP of the fluid containing structure 100, which constellation CON_PHOP(p_u,PHOP(PRV’), p_d,PHOP(PRV’)) of momentarily measured pressures p_u,PHOP(PRV’), p_d,PHOP(PRV’) is related to which noise SND_201’(ENV(PRV’)), mo- mentarily present at the particular acoustic logger 201’ in the environment ENV(PRV’). Therein, the relationships ob- tained in the preparation phase PHP between the constella- tions CON_PHP(p_u,PHP(PRV’)(t), p_d,PHP(PRV’)(t)) on the one side and the noise data SND_201’,PHP(ENV(PRV’))(t) on the other side is expressed by the function f_PRV’ introduced above. In a sim- ple embodiment, the function f_PRV’ is realized as a look-up table which contains the measured noise data SND_201’,PHP(ENV(PRV’))(t) related to measured pressures p_u,PHP(PRV’)(t) and p_d,PHP(PRV’)(t)). In another simple embodi- ment, the function f_PRV’ is realized as a look-up table which contains the measured noise data SND_201’,PHP(ENV(PRV’))(t) re- lated to differences p_u,PHP(PRV’)(t)-p_d,PHP(PRV’)(t) of measured pressures p_u,PHP(PRV’)(t) and p_d,PHP(PRV’)(t)). However, other realizations are imaginable. This knowledge about the relationship between pressure con- stellations CON and actual noise, expressed by the function f, is utilized in the operation phase PHOP and in the leakage determination method LDM, respectively, especially in step LDM2 to determine the current noise measure NOI_201’(ENV(PRV’)). As indicated above, the function f estab- lished in the preparation phase PHP is applied in PHOP and 202207051 26 LDM to determine the noise measure NOI_201’(ENV(PRV’)) from mo- mentarily measured pressures p_u(PRV’), p_d(PRV’): The function f first uses the pressures p_u(PRV’), p_d(PRV’) measured with the pressure transducers 202’ to form a constellation CON(p_u(PRV’), p_d(PRV’)) and subsequently processes the formed constellation CON(p_u(PRV’), p_d(PRV’)) to determine the corre- sponding current noise measure NOI_201’(ENV(PRV’)). For exam- ple, the determined noise measure NOI_201’(ENV(PRV’)) might be a measure for the volume of the sound SND_201’,PHP(PRV’)(t1) measured in the preparation phase PHP for a certain constel- lation of pressures p_u,PHP(t1), p_d,PHP(t1) similar to the con- stellation of pressures momentarily measured. Typically, each potentially noise causing device 102 can be characterized by a specific function f₁₀₂, wherein different devices 102’, 102” might be characterized by different func- tions f_102’, f_102”. Therefore, such functions f₁₀₂ might be de- termined in the preparation phase PHP separately for each de- vice 102. In other words, a separate preparation phase PHP(102) is executed for each device 102, wherein each sepa- rate preparation phase PHP(102) proceeds as describe above w.r.t. PHP, i.e. continuous measurement of pressures p_u,PHP(102’)(t), p_d,PHP(102’)(t) and noise data SND_201’,PHP(ENV(102’))(t) over time, forming constellations CON(p_u,PHP(102’)(t), p_d,PHP(102’)(t)) from the measured pressure values p_u,PHP(PRV’)(t), p_d(PRV’)(t) for all or at least many t, and assigning or correlating the constellations CON(p_u,PHP(102’)(t), p_d,PHP(102’)(t)) with the noise data SND_201’,PHP(ENV(102’))(t). Therewith, a function f_102’ is created for each device 102’ in a respective preparation phase PHP(102’) which will be applied in regular operation PHOP, especially in step LDM2(102’) of the leakage determination method LDM(102’), with currently measured pressures p_u,PHOP(102’), p_d,PHOP(102’) in the surrounding SURR(102’) to provide the noise measure NOI_201’(ENV(102’)). For the sake of clarity, it might be mentioned that different preparation phases for different devices might be executed in parallel. 202207051 27 In any case, the preparation phases might be performed and controlled by the evaluation system 220. In the above, it has not been specified how many acoustic loggers 201’ should be reasonably applied for the leakage de- termination method LDM(102’) for a particular device 102’ and/or for the respective preparation phase PHP(102’). Method LDM(102’) as well as preparation PHP(102’) work with only one acoustic logger 201’ in the respective environment ENV(102’). However, preferably at least two acoustic loggers 201’ are foreseen in the environment ENV(102’) of a particular device 102’, measuring sound SND at the same time and forming a pair P201’ of acoustic loggers 201’. In that case, the correspond- ing sensor measurement data r_201-1’(SND), r_201-2’(SND) provided by those acoustic loggers 201-1’, 201-2’ for leakage detec- tion in the operation phase PHOP and in the ALD method exe- cuted in step LDM4(102’), respectively, can not only be used and analyzed for pure leakage detection as foreseen in ALD, but they can also be correlated in order to improve reliabil- ity of leakage detection and furthermore to localize a poten- tial leak LK based on knowledge of the topology of the fluid containing structure 100. The predefined conditions COND might be different for differ- ent devices 102. Thus, for each separate device 102 a specif- ic predefined condition COND(102) might be applicable. The extensions of the environments ENV might be different for different devices. Thus, each separate device 102 might be characterized by a specific environment ENV(102). For exam- ple, the technical details and properties of the device 102, the setup of a section of the fluid containing structure in which the particular device is located, as well as further properties would influence the reasonable extension of the environment ENV(102) of a particular device 102. Correspond- ingly, the extensions of the surroundings SURR might be dif- ferent for different devices so that each separate device 102 might be characterized by a specific surrounding SURR(102). 202207051 28 The leakage determination method LDM(102’) introduced here- with ensures high reliability because leakage detection it- self, e.g. via an ADL method, is only executed in case regu- lar noise SND(102’) is sufficiently low so that disturbance of the leakage detection can be excluded. The regular noise SND(102’) caused by a particular device 102’ is assessed based on a noise measure NOI(102’) which is derived from measured fluid properties, e.g. pressures p_u, p_d, in the sur- rounding SURR(102’) of the device 102’. While the present invention has been described above by ref- erence to various embodiments, it should be understood that many changes and modifications can be made to the described embodiments. It is therefore intended that the foregoing de- scription be regarded as illustrative rather than limiting, and that it be understood that all equivalents and/or combi- nations of embodiments are intended to be included in this description. Thus, the invention is not restricted to the above illustrated embodiments, but variations can be derived by a person skilled in the art without deviation from the scope of the invention.

Claims

202207051 29 Claims 1. Leakage determination process with an acoustic leak detec- tion (ALD) method for detection of a leak LK in a fluid con- taining structure (100), wherein an execution of the acoustic leak detection (ALD) method depends on fluid properties (p_u(102’), p_d(102’)) of a fluid in the fluid containing structure (100). 2. Leakage determination process according to claim 1, where- in - the fluid properties (p_u(102’), p_d(102’)) are processed with a predefined function f_102’ to determine a noise meas- ure NOI_201’(ENV(102’))=f_102’(p_u(102’), p_d(102’)), which repre- sents current noise SND_201’(ENV(102’)) in the fluid contain- ing structure (100), and - the execution of the acoustic leak detection (ALD) method depends on the determined noise measure NOI_201’(ENV(102’)). 3. Leakage determination process according to claim 2, where- in the function f_102’ is established in a preparation phase PHP of the leakage determination process by - measuring over time t the fluid properties (p_u,PHP(102’)(t), p_d,PHP(102’)(t)) and measuring, at the same time, noise data (SND_201’,PHP(ENV(102’))(t)) in the fluid containing structure (100), and - assigning the noise data (SND_201’,PHP(ENV(102’))(ti)) meas- ured at certain points ti in time t to fluid properties (p_u,PHP(102’)(ti), p_d,PHP(102’)(ti)) measured at the same points ti in time, so that the function f_102’ is established to provide, upon re- ceiving fluid properties (p_u(102’), p_d(102’)) as an input, those noise data SND_201’,PHP(ENV(102’)(tx) as an output NOI_201’(ENV(102’)) which have been assigned to measured fluid properties (p_u,PHP(102’)(tx), p_d,PHP(102’)(tx)) which are best matching with the input fluid properties (p_u(102’), p_d(102’)). 202207051 30 4. Leakage determination process according to any one of claims 1 to 3, wherein the leakage determination process is executed separately for each one of NENV≥1 environments ENV(102’) of NDEV≥1 particular potentially noise causing de- vices (102’) of the fluid containing structure (100). 5. Leakage determination process according to any one of claims 2 to 4, wherein the noise measure NOI_201’(ENV(102’))=f_102’(p_u(102’), p_d(102’)) represents current noise SND_201’(ENV(102’)) in the environment ENV(102’) of a particular potentially noise causing device (102’) of the fluid containing structure (100). 6. Leakage determination process according to claim 5, where- in the current fluid properties (p_u(102’), p_d(102’)) are measured in a surrounding SURR(102) of the particular device (102’) of the fluid containing structure (100), preferably both upstream and downstream of the particular device (102’). 7. Leakage determination process according to claim 6, where- in, - in a step LDM1(102’) the fluid properties (p_u(102’), p_d(102’)) in the surrounding SURR(102’) of the particular device (102’) are measured, - in a step LDM2(102’) the measured fluid properties (p_u(102’), p_d(102’)) are processed to determine the noise measure NOI_201’(ENV(102’)) by applying the function f_102’ with NOI_201’(ENV(102’))=f_102’(p_u(102’), p_d(102’)), - in a step LDM3(102’) the determined noise measure NOI_201’(ENV(102’)) is evaluated to decide whether a prede- fined condition COND(102’) is fulfilled, - in a step LDM4(102’) the acoustic leak detection (ALD) method is executed for the environment ENV(102’) of the particular device (102’) in case the predefined condition COND(102’) is fulfilled. 8. Leakage determination process according to any one of claims 4 to 7, wherein the function f_102’ is established for 202207051 31 the particular device (102’) and/or for its environment ENV(102’) in a preparation phase PHP of the leakage determi- nation process by - measuring over time t the fluid properties (p_u,PHP(102’)(t), p_d,PHP(102’)(t)) in the surrounding SURR(102’) of the par- ticular device (102’) and measuring, at the same time, noise data (SND_201’,PHP(ENV(102’))(t)) in the environment ENV(102’) of the particular device (102’), - assigning the noise data (SND_201’,PHP(ENV(102’))(ti)) meas- ured at certain points ti in time t to a constellation CON(p_u,PHP(102’)(ti), p_d,PHP(102’)(ti)) of fluid properties (p_u,PHP(102’)(ti), p_d,PHP(102’)(ti)) measured at the same points ti in time, so that the function f_102’ is established to provide, upon re- ceiving fluid properties (p_u(102’), p_d(102’)) as an input, those noise data SND_201’,PHP(ENV(102’)(tx) as an output NOI_201’(ENV(102’)) which have been assigned to the particular constellation CON(p_u,PHP(102’)(tx), p_d,PHP(102’)(tx)) of meas- ured fluid properties (p_u,PHP(102’)(tx), p_d,PHP(102’)(tx)) which matches best with the respective constellation CON(p_u(102’), p_d(102’)) of input fluid properties (p_u(102’), p_d(102’)). 9. Leakage determination process according to claim 8, where- in, for a particular environment ENV(102’), the acoustic leak detection (ALD) method applies, if executed, at least one acoustic logger (201’) located in the particular environment ENV(102’) to measure noise in the fluid in environment ENV(102’), wherein the same at least one acoustic logger (201’) is applied in the preparation phase PHP to measure the noise data (SND_201’,PHP(ENV(102’))(t)). 10. Leakage determination process according to any one of claims 2 to 9, wherein the acoustic leak detection (ALD) method is executed in the particular environment ENV(102’) in case the noise measure NOI_201’(ENV(102’)) fulfills a prede- fined condition COND(102’), wherein the predefined condition is defined such that 202207051 32 - a fulfillment of the predefined condition COND(102’) is achieved in case noise SND(100) in the environment ENV(102’) does not significantly disturb the acoustic leak detection (ALD) method. 11. Leakage determination process according to any one of claims 1 to 10, wherein - the particular device (102’) is a pressure reducing valve (PRV’) arranged in the fluid containing structure (100), - the fluid properties (p_u(102’), p_d(102’)) comprise a pres- sure p_u(102’) in the fluid upstream and a pressure p_d(102’) in the fluid downstream of the particular pressure reducing valve (PRV’). 12. Leakage determination system (200) for detection of a leak LK in a fluid containing structure (100) with one or more potentially noise causing devices (102), wherein the system (200) is configured to execute the leakage determina- tion process according to any one of claims 1 to 11 so that the execution of the acoustic leak detection (ALD) method is depending on fluid properties (p_u(102’), p_d(102’)) of the fluid in the fluid containing structure (100). 13. Leakage determination system (200) according to claim 12, comprising one or more particular sensors (202’) assigned to a particular potentially noise causing device (102’) of the fluid containing structure (100) for measuring the fluid properties (p_u(102’), p_d(102’)), wherein the sensors (202’) are arranged in the fluid containing structure (100) in a surrounding SURR(102’) of the particular device (102’). 14. Leakage determination system (200) according to claim 13, wherein at least one of the particular sensors (202’) is ar- ranged upstream of the particular device (102’) and at least one more of the particular sensors (202’) is arranged down- stream of the particular device (102’). 202207051 33 15. Leakage determination system (200) according to any one of claims 12 to 14, wherein - the particular device (102’) is a pressure reducing valve (PRV’) arranged in the fluid containing structure (100), - the particular sensors (202’) assigned to the particular device (102’) are pressure transducers for measuring pres- sures (p_u(102’), p_d(102’)) in the fluid, wherein the fluid properties (p_u(102’), p_d(102’)) comprise a pressure p_u(102’) in the fluid upstream and a pressure p_d(102’) in the fluid downstream of the particular pressure reducing valve (PRV’). 16. Fluid containing structure (100) comprising a leakage de- termination system according to any one of claims 12 to 15. 17. Fluid containing structure (100) according to claim 16, wherein the fluid is water or oil or gas and the structure (100) is a network for providing the fluid from one or more sources to one or more consumers.