METHOD AND SYSTEM FOR DETERMINING A FLUID PRESSURE AT A FLUID FLOW METER BEING INSTALLED IN A PIPE NETWORK

Abstract

A method determines a fluid pressure at a fluid flow meter installed in a pipe network that is supplied with fluid at a varying and/or variable input pressure. The method includes recording input pressure information for a determination of a difference between input pressures in a first considered time-window and second considered time-window, aggregating statistical data of a plurality of fluid flow events and/or fluid volume consumption events during the first considered time-window and the second considered time-window, providing the aggregated statistical data to a head-end system (HES) that has access to the input pressure information and determining, by the head-end system, a fluid pressure at the fluid flow meter based on a change in the aggregated statistical data between the first considered time-window and the second considered time-window, and the difference between the input pressures in the first considered time-window and the second considered time-window.

Claims

1. A method for determining a fluid pressure at a fluid flow meter that is installed in a pipe network that is supplied with fluid at a varying and/or variable input pressure, wherein the method comprises the steps of: recording input pressure information, wherein the input pressure information allows a determination of a difference between the input pressure in at least one first considered time-window and the input pressure in at least one second considered time-window; aggregating, in the fluid flow meter, at least during the at least one first considered time-window and during the at least one second considered time-window, statistical data of a plurality of fluid flow events and/or fluid volume consumption events; providing the aggregated statistical data in regular intervals and/or on demand to a head-end system that has access to the input pressure information; and determining, by the head-end system, a fluid pressure at the fluid flow meter based on: a change in the aggregated statistical data between the at least one first considered time-window and the at least one second considered time-window; and the difference between the input pressure in the at least one first considered time-window and the input pressure in the at least one second considered time-window.

2. The method of claim 1, wherein the change of the aggregated statistical data is a shift of one or more characteristic fluid flow peaks and/or fluid volume consumption peaks in an event histogram from the at least one first considered time-window to the at least one second considered time-window.

3. The method of claim 1, further comprising initiating a known change of the input pressure between the at least one first considered time-window and the at least one second considered time-window.

4. The method of claim 1, wherein aggregating the statistical data is performed during the same time-windows by a plurality of fluid flow meters that are installed in the pipe network.

5. The method of claim 1, wherein the fluid flow meter is a battery-powered ultrasonic flow meter, and the aggregated statistical data is provided by wirelessly transferring the data to the head-end system.

6. The method of claim 1, wherein the step of aggregating the statistical data comprises identifying repetitive characteristic fluid flow events caused by one or more consumer units that have a constant characteristic fluid flow profile and/or a constant characteristic fluid volume consumption profile and/or a constant characteristic hydraulic resistance profile.

7. The method of claim 1, wherein the step of aggregating the statistical data comprises identifying maximum fluid flow events.

8. The method of claim 1, wherein the fluid pressure (p) is determined as p=?p.Math.Q.sub.2.sup.2/(Q.sub.1.sup.2?Q.sub.2.sup.2) if the input pressure has changed by ?p=p?p.sub.1, wherein p.sub.1 is the input pressure during the first time-window, and wherein the aggregated statistical data shows a shift from one characteristic fluid flow Q.sub.1 during the first time-window to another characteristic fluid flow Q.sub.2 during the second time-window.

9. The method of claim 1, wherein the at least one first considered time-window and the at least one second considered time-window are selected to be time-windows between which the input pressure typically differs.

10. The method of claim 1, wherein the step of aggregating the statistical data comprises identifying characteristic fluid flow events by filtering associated characteristic fluid volume consumption events.

11. The method of claim 1, wherein the step of aggregating the statistical data comprises reducing the amount of data to parameters that are indicative of characteristic fluid flow events and/or characteristic fluid volume consumption events.

12. The method of claim 1, wherein the input pressure information further allows for a determination of a relative change (?p/p.sub.in) of the input pressure (p.sub.in) between the at least one first considered time-window and the at least one second considered time-window, wherein the fluid pressure at the fluid flow meter is only determined by the head-end system if the relative change (?p/p.sub.in) of input pressure (p.sub.in) is in the range of 10% to 25%.

13. The method of claim 1, wherein there is time span between the at least one first considered time-window and the at least one second considered time-window, wherein the input pressure has or was changed gradually and/or stepwise in the time span between the first considered time-window and the second considered time-window.

14. A system for determining a fluid pressure at a fluid flow meter that is installed in a pipe network that is supplied with fluid at a varying and/or variable input pressure, wherein the system comprises: a head-end system having access to input pressure information, wherein the input pressure information allows for a determination of a difference between the input pressure in at least one first considered time-window and the input pressure in at least one second considered time-window; and at least one fluid flow meter configured to aggregate, at least during the at least one first considered time-window and during the at least one second considered time-window, statistical data of a plurality of fluid flow events and/or fluid volume consumption events and to provide the aggregated data in regular intervals and/or on demand to the head-end system, wherein the head-end system is configured to determine a fluid pressure at the fluid flow meter based on: a change in the aggregated statistical data between the at least one first considered time-window and the at least one second considered time-window; and the difference between the input pressure in the at least one first considered time-window and the input pressure in the at least one second considered time-window.

15. The system of claim 14, wherein the change of the aggregated statistical data is a shift of one or more characteristic fluid flow peaks and/or fluid volume consumption peaks in an event histogram from the at least one first considered time-window to the at least one second considered time-window.

16. The system of claim 14, wherein a known change of the input pressure between the at least one first considered time-window and the at least one second considered time-window is initiated.

17. The system of claim 14, further comprising at least one further fluid flow meter to provide a plurality of flow meters configured to aggregate statistical data of a plurality of fluid flow events and/or fluid volume consumption events and to provide the aggregated data in regular intervals and/or on demand to the head-end system, wherein aggregating the statistical data is performed during the same time-windows by the plurality of fluid flow meters that are installed in the pipe network.

18. The system of claim 14, wherein the step of aggregating the statistical data comprises identifying repetitive characteristic fluid flow events caused by one or more consumer units that have a constant characteristic fluid flow profile and/or a constant characteristic fluid volume consumption profile and/or a constant characteristic hydraulic resistance profile.

19. The system of claim 14, wherein the fluid pressure (p) is determined as p=?p.Math.Q.sub.2.sup.2/(Q.sub.1.sup.2?Q.sub.2.sup.2) if the input pressure has changed by ?p=p?p.sub.1, wherein p.sub.1 is the input pressure during the first time-window, and wherein the aggregated statistical data shows a shift from one characteristic fluid flow Q.sub.1 during the first time-window to another characteristic fluid flow Q.sub.2 during the second time-window.

20. The system of claim 14, wherein the input pressure information further allows for a determination of a relative change (?p/p.sub.in) of the input pressure (p.sub.in) between the at least one first considered time-window and the at least one second considered time-window, wherein the fluid pressure at the fluid flow meter is only determined by the head-end system if the relative change (?p/p.sub.in) of input pressure (p.sub.in) is in the range of 10% to 25%.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In the drawings:

[0050] FIG. 1 is a schematic view showing an example of a pipe network supplying a plurality of consumer households with water;

[0051] FIG. 2 is a graph showing an example of a typical diagram of flow measured by a fluid flow meter over time;

[0052] FIG. 3 is a graph showing a typical characteristic fluid flow event as measured by a fluid flow meter over time;

[0053] FIG. 4 is a graph showing a high-resolution event histogram of counted fluid flow events with a bin size of 1 liter per hour;

[0054] FIG. 5 is a graph showing the events of FIG. 4 in a low-resolution event histogram by applying a bin size of 25 liters per hour;

[0055] FIG. 6 is a graph showing the events of FIG. 4 positioned in a two-dimensional plot according to flow and the time duration of the events, wherein a filtering of characteristic fluid volume consumption events is displayed;

[0056] FIG. 7 is a graph showing the filtered events of FIG. 6 in an event histogram with a bin size of 5 liters per hour;

[0057] FIG. 8a and FIG. 8b are graphs showing event histograms of counted fluid flow events with a bin size of 10 liters per hour, wherein FIG. 8a shows the events occurred during the first considered time-window and FIG. 8b shows the events occurred during the second considered time-window;

[0058] FIG. 9 is a graph showing an event histogram of counted fluid flow events with a bin size in flow of 10 liters per hour, wherein the events occurred during in the first considered time-window (light columns) and during the second considered time-window (dark columns);

[0059] FIG. 10 is a graph showing event distributions in a two-dimensional plot according to flow and time duration of the events;

[0060] FIG. 11 is a graph showing another event distribution in a two-dimensional plot according to ultrasonic phase shift and volume consumption per event;

[0061] FIG. 12 is a graph showing event distributions in a two-dimensional plot according to flow and time duration of the events, wherein the events occurred during the first considered time-window (shown as x-marks) and during the second considered time-window (shown as circular marks); and

[0062] FIG. 13 is a graph showing a diagram of the maximum fluid flow detected per day displayed over the days of the year.

DESCRIPTION OF PREFERRED EMBODIMENTS

[0063] Referring to the drawings, FIG. 1 shows a pipe network 1 of a water supply system for supplying a plurality of consumer households 3 with a fluid, e.g., water or gas. An operator of the pipe network 1, for example a utility provider, supplies the pipe network 1 with the fluid at a varying and/or variable input pressure p.sub.in. The input pressure p.sub.in may vary due to a dynamic behavior of the water supply system, or the input pressure p.sub.in may be varied on purpose by the utility provider. In any case, the utility provider has information about the input pressure p.sub.in that allows to determine the time and amount ?p of any change of input pressure p.sub.in.

[0064] Each consumer household 3 is equipped with a fluid flow meter 5 for determining the fluid volume consumption of each household and to communicate wirelessly consumption values to a head-end system HES for billing purposes. The idea is now to determine a fluid pressure at each consumer household 3 by use of the fluid flow meter 5 installed at the consumer household 3. Thereby, it is possible to give a utility provider information about the fluid pressure at each consumer household 3 without installing additional pressure sensors for measuring the fluid pressure.

[0065] FIG. 2 shows what a fluid flow meter 5 may typically measure during an hour of the day. There are longer periods of zero fluid consumption during which there is essentially zero or negligible fluid flow measured. There are, however, three distinct consumption events clearly visible. The first two consumption events are caused by a washing machine drawing a fluid flow of 320 liters per hour for about two minutes. The third consumption event was caused by a toilet use triggering a fluid flow of 195 liters per hour for about two minutes. The washing machine and the toilet are typical consumer units that have a characteristic consumption signature or consumption fingerprint. This means that the associated fluid flow events and/or fluid volume consumption events are repetitive and expected to occur quite often over a period of days, weeks and/or months.

[0066] FIG. 3 shows in more detail the toilet use triggering a fluid flow event of 195 liters per hour. The additional spike due to shortly washing hands while the toilet reservoir is refilling, can be ignored. The beginning of the event may be triggered by the steep rise in flow from zero to 195 liters per hour, whereas the end of the event may be indicated by the steep fall from 195 liters per hour to zero flow. The fluid flow event of 195 liters per hour may be an average flow during the event, wherein short spikes of overlaying additional consumption may be ignored.

[0067] FIG. 4 shows an event histogram in which the fluid flow events are counted per histogram bin, wherein the histogram bin size is one liter per hour. The events in FIG. 4 were counted over a period of several months with a stable input pressure p.sub.in. As can be seen, there are three distinct characteristic peaks in the histogram at 50 liters per hour, 200 liters per hour and 325 liters per hour. The flow meters 5 may be able to collect the data shown in FIG. 4 and to transmit wirelessly the histogram to the head-end system HES. However, the high-resolution histogram of FIG. 4 contains a lot of data, and the transmission would cause substantial battery power and uplink budget. In order to reduce the amount of data to be transmitted, the histogram could have a coarser binning as shown in FIG. 5 which shows a histogram with a histogram bin size of 25 liters per hour filled with the same events as shown in FIG. 4. The three peak positions are still clearly visible, and the amount of data is heavily reduced compared to the high-resolution histogram of FIG. 4.

[0068] Alternatively, or in addition, the amount of data to be transmitted can be reduced by applying a data filter to select only the most characteristic fluid flow events as shown in FIG. 6 which shows the events of FIGS. 4 and 5 positioned in a two-dimensional plot according to the event flow and the time duration of the event. If only the events within the dashed rectangles are selected, the amount of data to be transmitted can be heavily reduced. Furthermore, the signal-to-noise ratio in the remaining histogram can be significantly increased. The remaining histogram after the filtering is shown in FIG. 7 showing clear peaks at 50 liters per hour, 200 liters per hour and 325 liters per hour and almost no background noise.

[0069] FIG. 8a,b show the effect that a change ?p in the input pressure p.sub.in has on the positions of the characteristic fluid flow events in the event histograms. FIG. 8a shows the events in a first considered time-window during which the input pressure p.sub.in was stable. FIG. 8b shows the events in a second considered time-window during which the input pressure p.sub.in is smaller than during the first considered time-window. As can be seen, the central peak around 305 liters per hour shifted down to 275 liters per hour. The utility provider knows the difference ?p between the input pressure p.sub.in during the first considered time-window and the input pressure p.sub.in during the second considered time-window. The considered time-windows may be selected accordingly. It follows that the fluid pressure at the fluid flow meter 5, which aggregated the statistical data according to FIG. 8a,b, can be determined based on the peak shift from 305 liters per hour to 275 liters per hour. For example, if the pressure change between the first considered time-window and the second considered time-window was ?0.5 bar, the fluid pressure at the fluid flow meter 5 is 2.17 bar during the second time-window. During the first considered time-window, the fluid pressure at the fluid flow meter 5 was 2.67 bar.

[0070] FIG. 9 shows a similar situation with events from the first considered time-window and events from the second considered time-window in the same histogram, wherein the events of the first considered time-window are displayed as white columns and the events in the second considered time-window are displayed as black columns.

[0071] FIG. 10 shows another event distribution in a two-dimensional plot according to the event flow and the event duration. The event flow is here measured in gallons per minute (GPM). Distinct areas of high event density may be filtered to reduce the amount of aggregated statistical data to be sent to the head-end system HES. As explained before, such filtering also improves the signal-to-noise ratio for identifying characteristic peaks in the event histograms.

[0072] FIG. 11 shows another event distribution in a two-dimensional plot according to ultrasonic phase shift and volume consumption. In the example of FIG. 11, the fluid flow meter 5 is an ultrasonic flow meter that determines the fluid flow from a phase shift between ultrasonic waves travelling in the direction of fluid flow and against the direction of fluid flow. The ultrasonic phase shift is strongly correlated with the fluid flow, so that the fluid flow meter can use the phase shift as a measure for the fluid flow. The fluid volume consumption as displayed on the x-axis of FIG. 11 is determined as a product of the event flow and the event duration. As explained before, regions of high event density can be filtered to determine the peak positions in the histograms as accurately as possible.

[0073] FIG. 12 shows the events in the first considered time-window and events in the second considered time-window in the same two-dimensional plot according to event flow and event duration. The events in the first considered time-window are shown as x-marks and the events in the second considered time-window are shown as circles. As the input pressure p.sub.in has dropped between the first considered time-window and the second considered time-window, the events in the second considered time-window are shifted to lower event flows, which shows as a shift of the characteristic peaks in the event flow histograms.

[0074] FIG. 13 shows a different way to determine the fluid pressure at the fluid flow meter 5. FIG. 13 shows the maximum flow of the day recorded by the fluid flow meter 5 over the year. In the time of April to July, the maximum flow has a relatively stable base line at 600 liters per hour despite quite high fluctuations of the maximum flow. In mid-July, there is a holiday period of zero water consumption. As can be seen in FIG. 13, the maximum flow base line has dropped at the beginning of August to about 530 liters per hour. The reason for this drop of the maximum flow baseline is a drop of the input pressure p.sub.in by ?p. The fluid pressure p at the respective fluid flow meter 5 can then be determined based on the drop of the maximum flow baseline. For example, if the pressure change was known to be ?0.5 bar, the fluid pressure p at the fluid flow meter 5 can be determined to be p=?0.5 bar.Math.530.sup.2/(530.sup.2?600.sup.2)=1.78 bar during the second time-window. As the statistical uncertainties with the maximum flow base line are higher compared to determining the position of characteristic peaks in the event histograms, the method according to FIG. 13 is less preferred.

[0075] Where, in the foregoing description, integers or elements are mentioned which have known, obvious or foreseeable equivalents, then such equivalents are herein incorporated as if individually set forth. Reference should be made to the claims for determining the true scope of the present disclosure, which should be construed so as to encompass any such equivalents. It will also be appreciated by the reader that integers or features of the disclosure that are described as optional, preferable, advantageous, convenient or the like are optional and do not limit the scope of the independent claims.

[0076] The above embodiments are to be understood as illustrative examples of the disclosure. It is to be understood that any feature described in relation to any one embodiment may be used alone, or in combination with other features described, and may also be used in combination with one or more features of any other of the embodiments, or any combination of any other of the embodiments. While at least one exemplary embodiment has been shown and described, it should be understood that other modifications, substitutions and alternatives are apparent to one of ordinary skill in the art and may be changed without departing from the scope of the subject matter described herein, and this application is intended to cover any adaptations or variations of the specific embodiments discussed herein.

[0077] In addition, comprising does not exclude other elements or steps, and a or one does not exclude a plural number. Furthermore, characteristics or steps which have been described with reference to one of the above exemplary embodiments may also be used in combination with other characteristics or steps of other exemplary embodiments described above. Method steps may be applied in any order or in parallel or may constitute a part or a more detailed version of another method step. It should be understood that there should be embodied within the scope of the patent warranted hereon all such modifications as reasonably and properly come within the scope of the contribution to the art. Such modifications, substitutions and alternatives can be made without departing from the spirit and scope of the disclosure, which should be determined from the appended claims and their legal equivalents.

[0078] While specific embodiments of the invention have been shown and described in detail to illustrate the application of the principles of the invention, it will be understood that the invention may be embodied otherwise without departing from such principles.

LIST OF REFERENCE CHARACTERS

[0079] 1 pipe network [0080] 3 consumer household [0081] 5 fluid flow meter [0082] HES head-end system [0083] Q.sub.1 fluid flow in the first considered time-window [0084] Q.sub.2 fluid flow in the second considered time-window [0085] p fluid pressure at the fluid flow meter [0086] p.sub.in input pressure