Method and system for determining a fluid property of a fluid in a fluid system

Abstract

A method for determining a viscosity, and / or a property correlated with the viscosity, of a fluid of a fluid system, the method comprising: using a vortex flow sensor to obtain a plurality of measured values, the measured values being indicative of a degree of flow of the fluid; determining, from the plurality of measured values, a measure of dispersion of the measured values; determining the viscosity, and / or the property correlated with the viscosity, of the fluid from the determined measure of dispersion.

Description

[0001] Method and system for determining a fluid property of a fluid in a fluid system

[0002] TECHNICAL FIELD

[0003] The present invention relates to methods for determining a fluid property of a fluid, in particular the viscosity of the fluid, or a flow speed of the fluid, or an amount of a constituent of the fluid. The invention further relates to an apparatus and a computerprogram for performing the method.

[0004] BACKGROUND

[0005] Flow measurements are important in many applications that involve fluid flow.

[0006] Moreover, estimating viscosity is important in many flow sensor applications because flow measurements can be significantly impacted by the viscosity of the fluid medium, particularly when the viscosity exceeds a viscosity level of 1 mm2 / s.

[0007] Yet further, certain constituents of a fluid can affect the viscosity and / or other properties of the fluid. Therefore it is generally desirable to determine the amount of such constituents present in a fluid.

[0008] For example, flow sensors are often integrated into water pump systems that operate in diverse environments, where ambient temperatures can vary widely. To protect these systems against freezing, it is common to add an antifreeze agent, typically glycol, to the water. A water-glycol mixture has a higher variation in kinematic viscosity: Kinematic viscosity increases as the media temperature drops and, especially in low-temperature conditions, this affects the flow sensor's accuracy. Therefore, it is desirable to estimate the viscosity and / or the glycol concentration in flow sensor applications, as this allows for accurate flow measurement corrections and / or provides insights into the level of freeze protection afforded to the system.

[0009] US 2009 / 0165565 discloses a method for determining the viscosity of a water-glycol mixture. This prior art method bases the viscosity measurement on a measurement of the smallest flow speed in a channel, at which vortices arise for the first time behind a body that is arranged in the channel. This speed is used as a measure for the viscosity of the flowing water-glycol mixture. From the measured viscosity, the process further derives the glycol concentration of the mixture.

[0010] However, this method requires that the fluid flow speed is controlled to a small flow which is typically considerably smaller than the desired flow during normal operation of the fluid system. Accordingly, the measurement process often requires a certain flow control protocol for the purpose of the viscosity measurement, which may require interruption of the normal / useful operation of the fluid system, e.g. in order to intermittently reduce the flow below an operationally useful degree, solely for the purpose of the viscosity measurement.

[0011] It is therefore desirable to provide a viscosity measurement, and / or a measurement of a property correlated with the viscosity of the fluid, that has little impact on the normal operation of the fluid system.

[0012] It is further desirable to provide a viscosity measurement, and / or a measurement of a property correlated with the viscosity of the fluid, that can be performed frequently during normal operation of a fluid system. It is further desirable to provide a viscosity measurement, and / or a measurement of a property correlated with the viscosity of the fluid, that can be performed by a flow sensor without requiring complex additional sensor equipment.

[0013] It is further desirable to provide a viscosity measurement, and / or a measurement of a property correlated with the viscosity of the fluid, that provides real-time or quasi-real time measurements.

[0014] SUMMARY

[0015] On the above background, it remains desirable to provide a method for determining the viscosity, and / or a property correlated with the viscosity, of a fluid that solves one or more of the above problems and / or other problems, and / or that has other benefits, or that at least provides an alternative to existing solutions.

[0016] According to one aspect, disclosed herein are embodiments of a method for determining a viscosity, and / or a property correlated with the viscosity, of a fluid of a fluid system. The method comprises:

[0017] - using a vortex flow sensor to obtain a plurality of measured values, the measured values being indicative of a degree of flow of the fluid;

[0018] - determining, from the plurality of measured values, a measure of dispersion of the measured values;

[0019] - determining the viscosity, and / or the property correlated with the viscosity, of the fluid from the determined measure of dispersion.

[0020] The inventors have realized that the measured values, which are obtained using a vortex flow sensor, may not only be used to obtain a measurement of the degree of flow of the fluid but also to obtain a measurement of the viscosity of the fluid and / or a measurement of a property correlated with the viscosity of the fluid. In particular, the inventors have realized that the dispersion of the measured values is correlated to the viscosity of the flowing fluid and, hence with other properties correlated with the viscosity. For the purpose of the present disclosure, the term dispersion refers to the scattering of the measured values around a mean value, i.e. the extent to which the distribution of measured values is stretched or squeezed.

[0021] In particular, the inventors have realised that such a correlation between the dispersion and the viscosity and / or between the dispersion and a property correlated with the viscosity may be established over a range of flow speeds, temperatures and viscosities. Therefore, in a fluid system, measurements based on the dispersion of measured values may be used to determine the viscosity or related properties over a range of operating conditions of the fluid system. Accordingly, the measurements can be performed with less need to adjust the operation of the system in order to be able to perform a viscosity measurement. Generally, the determination of the viscosity or viscosity-related property from the determined measure of dispersion may be performed based on a model relating the measure of dispersion to the viscosity or viscosity-related property. The model may be a predetermined model. The model may be a regressions model, a trained machine-learning model or another suitable model.

[0022] Properties of the fluid that are correlated with the viscosity include properties affecting the viscosity and properties affected by the viscosity. Examples of such properties correlated with the viscosity include the amount of a constituent of the fluid that affects the viscosity of the fluid. Other examples include the freezing point of the fluid, which again may be affected by one or more constituents of the fluid. Properties correlated to the viscosity will also be referred to as viscosity-related properties.

[0023] A suitable measure of dispersion is the variance or standard deviation (STD) of a plurality of measured values or a parameter indicative of the STD. Alternative measures of dispersion include a difference between a maximum and a minimum measured value, optionally normalized by e.g. a mean measured value or otherwise, of the plurality of measured values.

[0024] As the measured values are obtained using a vortex flow sensor, the measurement may be based on sensor data acquired by a vortex flow sensor that is used to measure the degree of flow of the fluid, i.e. without the need for complex additional sensors. Nevertheless, in some embodiments, an additional temperature sensor may be useful to increase the accuracy of the measurement of the viscosity or of a property related to the viscosity, as will be described below. The measured degree of flow may be expressed as a flow rate or as a flow speed or as another suitable flow measure.

[0025] Generally, using the vortex flow sensor to obtain the plurality of measured values may include measuring the measured values, e.g. when the process is performed by a vortex flow sensor. Alternatively, using the vortex flow sensor to obtain the measured values may comprise receiving the measured values, in particular receiving the measured values directly or indirectly from the vortex flow sensor, or otherwise. Alternatively, using the vortex flow sensor to obtain the plurality of measured values may comprise receiving sensor data directly or indirectly from the vortex flow sensor, and deriving the measured values from the received sensor data. Vortex flow sensors are also referred to as vortex flowmeters. The measured values are indicative of a degree of flow, i.e. a measured degree of flow may be derived from one or more of the measured values. In some embodiments, each of the measured values may be indicative of a measured degree of flow while, in other embodiments, the measured degree of flow is derivable from a plurality of the measured values, e.g. from a subset of the obtained plurality of measured values or from the entire plurality of measured values. Accordingly, in some embodiments, the method comprises determining a measured degree of flow from the plurality of obtained measured values. The inventors have found that measured values obtained using a vortex flow sensor are particularly useful for measuring viscosity or fluid properties related to the viscosity. A vortex flow sensor typically comprises a body arranged such that a fluid flows past the body. The body is further configured to cause vortices to be formed in the fluid when the fluid passes the body. The vortex flow sensor detects the vortices and, in particular a frequency at which vortices are formed and, in particular, detached from the body as a result of the fluid flowing past the body. The determined frequency of vortex formation is correlated with the actual flow speed at which the fluid passes the body and can be used to measure the flow speed or another measure of the degree of flow, e.g. the flow rate. The vortex flow sensor may detect the formation and detachment of vortices by measuring a pressure, in particular a differential pressure between opposite sides of the body, and / or by detecting a deflection of the body, and / or otherwise. In some embodiments, the vortex flow sensor comprises or is operationally coupled to conduit that defines a channel through which the fluid flows. The vortex flow sensor may thus further comprise the body, which may be arranged in the channel so as to cause the fluid to pass the body when the fluid flows thorough the channel. The body causes vortices to be formed in the fluid when the fluid passes the body during the fluid's passage through the channel.

[0026] Generally, the measured values may be sensor data obtained by the vortex flow sensor and / or the measured values may be derived from such sensor data. For example, a vortex flow sensor may output sensor data indicative of measured pressure values or indicative of deflection values. A frequency of vortex formation and / or another measure of the degree of flow may be derivable from the sensor data, e.g. from a series of pressure values or from a series of deflection values. Accordingly, the measured values may be pressure values, deflection values, or the like. Alternatively, the measured values may be frequency values, flow rate values, or the like, which may be derived from the sensor data, e.g. from pressure values, deflection values, or the like.

[0027] In some embodiments, the measured values are indicative of at least one feature of vortex formation, in particular vortex formation caused by a vortex flow sensor to occur in a fluid that flows through the vortex flow sensor. The at least one feature may include a degree of vortex formation, in particular a frequency of vortex formation, e.g. the frequency of pressure changes, which has been found to provide an accurate estimate of the viscosity. Alternative or additional features include the amplitude of vortex formation, e.g. the amplitude of the measured pressure differences. The at least one feature may thus be measured by a vortex flow sensor or derived from sensor data obtained by the vortex flow sensor. The measured values may comprise measured frequencies of vortex formation or other measured feature values, or the measured values may comprise measured values from which frequencies of vortex formation or other feature values are derivable.

[0028] The inventors have found that there is correlation between the viscosity of the fluid and how stable the vortex frequency measured by a vortex flow sensor is, e.g. as represented by the standard deviation or other measure of dispersion of a sequence of vortex frequency measurements. At higher flow and lower viscosity, e.g. due to higher fluid temperature for the same fluid, the dispersion of the frequency measurements decreases and measured frequency spectra of the vortex creation become more alike.

[0029] In order to accurately determine the dispersion of the measured values that can be correlated to the viscosity of the fluid, it is preferred that the measured values are obtained based on measurements made during a period of stable operational conditions, in particular during a period of stable flow conditions and / or stable fluid temperatures. Stable flow conditions may often be ensured during the normal operation of the fluid system, e.g. during operation of a pump of the fluid system at a constant pump speed or otherwise such that the nominal or expected actual flow is constant, or does not vary more than by a predetermined margin, over a period of time where the dispersion-based measurement is performed. Alternatively or additionally, the process may monitor one or more operational flow conditions and select a measurement period where the monitored one or more flow conditions, in particular the flow rate and / or fluid temperature, are stable, i.e. are constant or do not vary more than by a predetermined margin.

[0030] In some embodiments, the method comprises performing the determining of the viscosity, and / or the property correlated with the viscosity, of the fluid from the determined measure of dispersion conditioned on a current operational state of the fluid system, in particular conditioned on a current magnitude and / or stability of the measured flow. Accordingly, the process may ensure that the viscosity value (and / or the value of another property correlated with the viscosity) is obtained during an operational state of the fluid system where a suitable correlation between the measure of dispersion and the viscosity (or other property correlated with the viscosity) has been established.

[0031] In some embodiments, the plurality of measured values represent a time series of measured values acquired during a measurement period. In some embodiments, the method comprises selecting a measurement period such that the measured flow is substantially constant during the selected measurement period, e.g. such that the measured flow does not vary more than a predetermined absolute or relative margin. Accordingly, the dispersion of measurement values during such a period provide a more accurate indicator for the viscosity as variations in measured values are not caused by variations of the actual flow speed. In some embodiments, the method comprises selecting a measurement period such that one or more operational conditions associated with the fluid flow fulfil one or more predetermined criteria, in particular are within a predetermined operational range during the selected measurement period, in particular within a predetermined operational range for which a correlation between the dispersion of measured values and the viscosity (or a related property) has previously been established and where the established correlation is suitable for determining the viscosity (or related property) from the observed dispersion. Examples of operational conditions include the flow speeds / rates and the fluid temperature. As the specific degree and / or form of correlation between viscosity (or a related property) and the determined dispersion may depend on the operational state, it may be useful to establish correlation models for one or more ranges of operational state and perform the measurement process when the system operates in the corresponding range of operational conditions, thereby providing a particular accurate measurement of the viscosity or viscosity related properties. For example, the correlation between viscosity and the dispersion of measured values may be particularly pronounced for some ranges of flow speeds, e.g. at lower flow speeds, than for other ranges of flow speeds, e.g. at high flow speeds. It will be appreciated that the ranges may depend on the type of sensor used and may be established during a suitable calibration process based on reference measurements for a particular type or group of sensors. The selected ranges of operational conditions may include operational conditions at which the fluid system typically operates at least during certain periods of time, thereby allowing the measurement of viscosity or of viscosity related properties to be performed without having to affect the normal operation of the fluid system. Nevertheless, if desired, the process may also deliberately control the fluid system to operate at one of the selected operational states for the purpose of performing the measurement of the viscosity or viscosity-related property, e.g. during system start-up or at predetermined intervals or otherwise. For example, the determination of the viscosity or viscosity-related property may be performed, when the fluid system, e.g. a reversible heating appliance such as a heat pump or a chiller, operates at a constant actual flow and, optionally, at a constant fluid temperature, and, optionally, where the actual flow is in a predetermined range. During such operation, the measured values may be recorded and, if the operation at the constant flow and, optionally, temperature, continues for at least a predetermined period of time (e.g. for more than 5 minutes, or more than 10 minutes, or for another suitable period), the determination of the viscosity of viscosity-related property is performed based on the recorded measured values during said period. In many fluid systems, such periods of operation at stable operational conditions occur regularly or may at least be caused to occur without significantly affecting the normal operation of the fluid system. An example of such an operational conditions may e.g. be a forced operational cycle of a reversible heating appliance including, e.g. including a heating cycle and a defrost operation, or it could be by merely monitoring the system during normal operation where new measurements of the viscosity or viscosity-related property are populated when the process successfully completes a determination of the viscosity or viscosity-related property, i.e. when the fluid systems operates under stable operational conditions for a period of time sufficiently long to compete the determination of the viscosity or viscosity-related property .

[0032] The monitoring may be based on measured values and / or on control signals from a control system controlling the fluid system. For example, the control signals may indicate a start and / or stop of an operational cycle where stable operational conditions can be expected. Alternatively or additionally, the method may comprise controlling the one or more operational conditions to fulfil the one or more predetermined. Accordingly, the method may comprise:

[0033] - monitoring and / or controlling one or more operational conditions associated with the fluid flow of the fluid, in particular the degree of flow and / or the fluid temperature, - selecting a measurement period responsive to the monitored and / or controlled one or more operational conditions fulfilling one or more predetermined criteria; and wherein determining the measure of dispersion comprises determining the measure of dispersion from from the plurality of measured values obtained during the selected measurement period.

[0034] The fluid may be a liquid, such as water or a liquid including water as a major constituent, e.g. water and at least one other constituent. The other constituent may be a constituent that affects the viscosity of the liquid. In some embodiments the other constituent is an antifreeze agent, such as glycol, e.g. ethylene glycol and / or propylene glycol. Other examples of antifreeze agents include methanol. In some embodiments, the liquid is a heat transfer medium having one or more constituents.

[0035] In some embodiments, the property correlated with the viscosity is an amount of a constituent of the fluid, the constituent affecting the viscosity of the fluid. Accordingly, the method may comprise determining the amount of the constituent from at least the determined dispersion and / or the determined viscosity, and optionally further from a temperature of the fluid. The determination of the amount of the constituent may be performed based on a model relating the amount of the constituent to the dispersion and / or to the determined viscosity, and optionally further to a temperature of the fluid. The model may be a predetermined model. The model may be a regressions model, a trained machine-learning model or another suitable model. In some embodiments, the property correlated with the viscosity is a freezing point of the fluid, and wherein determining the freezing point comprises determining the freezing point from at least the determined dispersion and / or the determined viscosity, and optionally further from a temperature of the fluid. In some embodiments, the amount of antifreeze agent in the fluid may be expressed as a concentration of antifreeze agent or as a resulting level of freeze protection, e.g. as a resulting freezing point or freeze protection temperature of the fluid including the antifreeze agent, or otherwise.

[0036] The determination of the viscosity or viscosity-related property from the determined measure of dispersion may be performed by using a pre-determined correlation, e.g. a correlation determined based on measurements, between the measure of dispersion and the viscosity. For example, such measurements may be performed for a particular type of vortex flow sensor and used to establish a regression model or other suitable correlation model of the correlation between the measure of dispersion and the viscosity for the particular type of vortex flow sensor. In some embodiments, the regression model is a linear regression. In some embodiments, the correlation model includes more than one regression model, e.g. regression models applicable for respective operational ranges of the fluid system, e.g. respective fluid temperatures, flow speeds / rates and / or the like.

[0037] In some embodiments, the method may further comprise performing a flow measurement using the measured values and further based on the determined dispersion, in particular by determining a flow offset from the determined dispersion. The flow measurement may provide a flow measurement value, in particular a flow measurement value indicative of the degree of flow, e.g. a flow speed or flow rate.

[0038] In some embodiments, performing the flow measurement comprises:

[0039] - determining, from the plurality of measured values, a flow measurement value;

[0040] - determining an adjusted flow measurement value from determined flow measurement value and from the determined dispersion, in particular by determining a flow offset from the determined dispersion. In particular, the determination of the adjusted flow measurement value may be based on a predetermined correlation between one or more adjustment values, e.g. an offset, and the determined viscosity. Accordingly, a more accurate flow measurement, that accounts for viscosity-related in accuracy of the flow measurement, in particular when performed by vortex flow sensors, may be achieved. The predetermined correlation may be represented by a suitable regression model, e.g. a linear regression, or otherwise. It will be appreciated that the adjustment value for adjusting the flow measurement value may be determined directly or indirectly from the determined measured of dispersion. For example, the determination of the adjusted flow measurement value may be based on a predetermined correlation between the determined measure of dispersion and the adjustment value, by which the flow measurement value is to be adjusted. Alternatively, the adjustment value may be determined by initially determining the viscosity from the determined measure of dispersion and subsequently determining the adjustment value from the thus determined viscosity. In such embodiments, the adjustment value may be determined from a predetermined correlation between viscosity and adjustment values.

[0041] Similarly, the determination of an amount, in particular a concentration, of a constituent of the fluid may be based on a predetermined correlation between the viscosity and the amount / concentration. Alternatively, the determination of the amount / concentration of a constituent of the fluid may be based on a predetermined correlation between the determined measure of dispersion and the amount / concentration.

[0042] In some embodiments, the determination of the amount / concentration may be based on a plurality of viscosity measurements (or a plurality of dispersion measurements), obtained at respective fluid temperatures.

[0043] Generally, the viscosity may be a kinematic viscosity.

[0044] The present disclosure relates to different aspects including the method described above and in the following, corresponding apparatus, systems, methods, and / or products, each yielding one or more of the benefits and advantages described in connection with one or more of the other aspects, and each having one or more embodiments corresponding to the embodiments described in connection with one or more of the other aspects and / or disclosed in the appended claims.

[0045] In particular, according to one aspect, disclosed herein are embodiments of a method of performing a flow measurement of a flowing fluid. The method comprises:

[0046] - using a vortex flow sensor to obtain a plurality of measured values, the measured values being indicative of a degree of flow of the fluid;

[0047] - determining, from the plurality of measured values, a flow measurement value;

[0048] - determining, from the plurality of measured values, a measure of dispersion of the measured values;

[0049] - determining an adjusted flow measurement value, in particularly a viscosity-adjusted flow measurement value, from determined flow measurement value and from the determined dispersion, in particular by determining a flow offset from the determined dispersion.

[0050] As discussed above, flow measurements by vortex flow sensors can be impacted by the viscosity of the fluid whose flow is to be measured. By determining an adjusted flow measurement value, in particularly a viscosity-adjusted flow measurement value, from the determined flow measurement value and from a determined dispersion of the underlying measured values, a more accurate flow measurement may be performed that accounts for the viscosity of the fluid.

[0051] In some embodiments, the method comprises:

[0052] - determining the viscosity of the fluid from the determined measure of dispersion, - determining the adjusted flow measurement value from the flow measurement value and from the determined viscosity, in particular by determining a flow offset from the determined viscosity.

[0053] According to another aspect, disclosed herein are embodiments of a method of determining an amount, in particular a concentration, of a constituent of a fluid.

[0054] In some embodiments, determining the amount comprises:

[0055] - determining the viscosity of the fluid from the determined measure of dispersion,

[0056] - determining the amount of a constituent of the fluid from the determined viscosity and, optionally, from a temperature of the fluid.

[0057] Embodiments of the methods disclosed herein may be computer-implemented.

[0058] Accordingly, further disclosed herein are embodiments of a data processing system configured to perform the steps of one or more of the methods described herein. In particular, the data processing system may have stored thereon program code adapted to cause, when executed by the data processing system, the data processing system to perform the steps of one or more of the methods described herein.

[0059] Embodiments of the data processing system may be embodied as a data processing circuit that is integrated with the vortex flow sensor, or it may partly or completely be implemented external to the vortex flow sensor. An integrated data processing circuit may be embodied as a suitably programmed microprocessor, as an ASIC, and / or other suitable processing unit. Accordingly, a vortex flow sensor apparatus may include a vortex flow sensor and a data processing circuit. The vortex flow sensor and the data processing circuit may be accommodated within a single housing, i.e. the vortex flow sensor apparatus may comprise a housing accommodating the vortex flow sensor and the data processing circuit. Alternatively, the vortex flow sensor and the data processing circuit (or a part thereof) may be provided in separate housings.

[0060] The data processing system may be implemented as a single computer or other data processing device, or as a distributed system including multiple computers and / or other data processing devices, e.g. a client-server system, a cloud-based system, etc. The data processing system may include a data storage device for storing the computer program and, optionally, sensor data. The data processing system may include a communications interface for receiving the measured values and / or other sensor data, e.g. from a vortex flow sensor. The data processing system may receive the the measured values and / or other sensor data directly or indirectly from the vortex flow sensor via a suitable wired or wireless communicative connection, e.g. via a suitable communications network, or otherwise.

[0061] Yet another aspect disclosed herein relates to embodiments of a computer program configured to cause a data processing system to perform the acts of the method described above and in the following. A computer program may comprise program code means adapted to cause a data processing system to perform the acts of one or more of the methods disclosed above and in the following when the program code means are executed on the data processing system. The computer program may be stored on a computer-readable storage medium, in particular a non-transient storage medium, or embodied as a data signal. The non-transient storage medium may comprise any suitable circuitry or device for storing data, such as a RAM, a ROM, an EPROM, EEPROM, flash memory, magnetic or optical storage device, such as a CD ROM, a DVD, a hard disk, and / or the like.

[0062] Yet another aspect disclosed herein relates to embodiments of an apparatus comprising a vortex flow sensor and a data processing system as disclosed herein, the data processing system being configured to receive the sensor data from the vortex flow sensor.

[0063] Yet another aspect disclosed herein relates to embodiments of a fluid system comprising such an apparatus. Generally, a fluid system may comprise one or more pipes or other forms of conduits through which fluid can flow, and the various aspects disclosed herein provide measurements of the flow of the fluid through the one or more conduits and / or measurements of the viscosity and / or another property correlated with the viscosity of the fluid flowing through the one or more conduits. Embodiments of a fluid systems may include a pump for providing fluid flow through the one or more conduits. Examples of fluid systems include a heating or cooling system that uses a fluid as a medium to transport heat. Examples of such heating or cooling systems include reversible heating appliances, such as heat pump systems, chillers, etc. Other examples of fluid system include water pump systems and fluid-based solar systems.

[0064] BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Preferred embodiments will be described in more detail in connection with the appended drawings, where

[0066] FIGs. 1A-B schematically illustrates an embodiment of a fluid system. FIG. 2 schematically illustrates an embodiment of a vortex flow sensor.

[0067] FIG. 3 schematically illustrates a block diagram of an embodiment of a process for determining the viscosity, glycol concentration and a measured flow of a fluid.

[0068] FIGs. 4A-C schematically illustrate the distribution of measured vortex frequencies of fluids having respective viscosities.

[0069] FIGs. 5A-D schematically illustrate an example of the relationship between the dispersion of measured vortex frequencies and the viscosity of a fluid FIG. 6 schematically illustrates an example of the relationship between viscosity, glycol concentration and temperature.

[0070] FIG. 7 schematically illustrates an example of the relationship between flow measurement errors and viscosity.

[0071] FIGs. 8A-B schematically illustrate an example of the correction of flow measurements based on measured viscosities.

[0072] FIGs. 9A-C schematically illustrate another example of the relationship between the dispersion of measured vortex frequencies and the viscosity of a fluid.

[0073] FIG. 10 schematically illustrates a flow diagram of an embodiment of a process for determining a viscosity-related property of a fluid.

[0074] DETAILED DESCRIPTION

[0075] FIGs. 1A-B schematically illustrates an embodiment of a fluid system, in particular a heat pump system. FIG. 1A shows a schematic view of the heat pump system while FIG. IB shows an enlarged view of a part of the system. The heat pump system comprises an outdoor module 6 and an indoor module 3. The outdoor module 6 comprises a condenser 5, which is connected with the indoor module 3 via a condenser loop 4 of pipes or other conduits. The heat pump system further comprises a pump 2 for moving the fluid between the indoor module 3 and the outdoor module 6. The heat pump system further comprises a flow sensor 1 configured to measure the fluid flow through the condenser loop 4. The flow sensor 1 is further configured to measure the viscosity of the fluid flowing through the flow sensor, as will be described in more detail below.

[0076] Alternatively or additionally, the flow sensor 1 may be configured to measure a property correlated with the viscosity of the fluid. It will be appreciated that the heat pump system may include additional or alternative components, such as an indoor heat exchanger, various valves, control circuitry etc. In the example of FIGs. 1A-B, the pump 2 and the flow sensor 1 are shown integrated into the indoor module 3. However, it will be appreciated that the flow sensor and / or the pump may be provided externally to the indoor module. Similarly, the pump 2 and the flow sensor 1 are shown as separate components, individually and separately arranged along the condenser loop 4. However, it will be appreciated that the flow sensor may be integrated into the pump or into another component of the system. The system may further include a temperature sensor (not explicitly shown) for measuring the temperature of the fluid at a location in the condenser loop 4. The temperature sensor may be integrated into the flow sensor 1, into the pump 2, into the indoor module 3, into the outdoor module 6, provided as a separate sensor, or otherwise.

[0077] The flow sensor 1 is a vortex flow sensor, e.g. as will be described below with reference to FIG. 2, or otherwise.

[0078] The fluid used in typical heat pump systems is water with a suitable amount of antifreeze agent to avoid freezing of the water. A frequently used antifreeze agent is glycol, such as ethylene glycol or propylene glycol. However, other antifreeze agents may be used instead.

[0079] It is generally desirable to be able to determine the concentration of the antifreeze agent in the fluid, e.g. to be able to ascertain that the actual concentration is sufficient for effective protection against freezing while avoiding use of unnecessary amounts of antifreeze agent, e.g. when replenishing antifreeze agent. The amount of antifreeze agent in the fluid is correlated with the viscosity of the fluid. Unnecessarily high amounts of antifreeze agent may result in unnecessary power consumption of a pump pumping the fluid and / or may have other undesirable effects. Moreover, the flow measurements provided by the flow sensor 1 may include errors that depend on the viscosity of the fluid, which in turn depends on the temperature of the fluid and on the concentration of antifreeze agent.

[0080] Accordingly, it is desirable to measure the viscosity of the fluid. To this end, the fluid system comprises processing circuit 16 configured to perform a determination of the viscosity and / or of a viscosity-related property of the fluid in the condenser loop 4. The processing circuit 16 is operationally coupled to the flow sensor 1 and obtains sensor data from the flow sensor 1. While shown as a separate block in FIG. 1, the processing circuit 16 may be integrated into the flow sensor 1 and / or into another component of the fluid system, e.g. into the pump, the indoor module or the outdoor module. Yet further, the processing circuit may be distributed between two or more of the components of the fluid system, or it may be implemented by a remote system, a cloud system or the like. The processing circuit 16 may comprise analogue and / or digital signal processing circuitry and comprise one or more suitably programmed microprocessors, one or more application-specific integrated circuits (ASIC) or as another suitable electronic circuitry, or a combination thereof. The processing circuit is configured to perform an embodiment of determining the viscosity and / or a viscosity-related property as described herein, e.g. the process of FIG. 10 and / or FIG. 3 or otherwise.

[0081] FIG. 2 schematically illustrates an embodiment of a vortex flow sensor, generally designated by reference numeral 1. The vortex flow sensor 1 comprises a flow pipe section 11 that defines a flow channel 12 through which the fluid passes along the direction indicated by the arrow 13. Accordingly, the vortex flow sensor may be provided as an inline sensor along a pipe or other conduit, where all fluid flowing through the pipe or other conduit passes through the channel 12 defined by the vortex flow sensor. The vortex flow sensor 1 further comprises a vortex generating body 14 that is positioned in the flow channel 12 such that the moving fluid passes the vortex generating body. The vortex generating body is also referred to as bluff body. When the fluid flows past the bluff body 14 vortices 17 are created in the fluid.

[0082] In particular, when such a body is subjected to onflow with a low speed, then the flow runs in a substantially laminar manner with a low Reynolds number. With an increasing speed (higher Reynolds number), stationary vortices occur. When the actual flow speed is increased further, the vortices detach from the body and form a so-called vortex street downstream from the body. The detachment frequency of the vortices may be determined by way of the Strauhal number, which is dependent on the shape of the body. For the purpose of the present description, the term vortex formation is intended to refer to the formation of vortices that detach from the body. On account of the linear relation of the detachment frequency and the flow speed, this physical effect is utilized for the flow measurement with non-abrasive, low viscosity media. For the purpose of the present description, the detachment frequency will also be referred to as frequency of vortex formation or just vortex frequency or simply frequency.

[0083] Accordingly, the vortex flow sensor 1 further comprises a pressure sensor 15 for sensing pressure variations caused by the created vortices. To this end, the pressure sensor 15 may be a differential pressure sensor. The pressure sensor may comprise a pressure sensitive die 151 or membrane. Other examples of vortex flow sensors may detect vortex formation in a different manner, e.g. by detecting deflections of a deflecting element that are caused by the vortices, or otherwise.

[0084] The vortex flow sensor may further comprise a processing circuit 16 coupled to the pressure sensor 15 and configured to process the sensor data from the pressure sensor to determine the measured flow of the fluid flowing through the flow channel 12. The processing circuit 16 may comprise analogue and / or digital signal processing circuitry and comprise one or more suitably programmed microprocessors, one or more application-specific integrated circuits (ASIC) or as another suitable electronic circuitry, or a combination thereof. The processing circuit 16 may be integrated into a housing of the vortex flow sensor. Alternatively or additionally, some or all of the signal processing may be performed by one or more processing units external to the vortex flow sensor, i.e. by one or more processing units not physically integrated into a housing of the vortex flow sensor. To this end, such external processing unit may be communicatively coupled to the pressure sensor 15 or to an internal processing circuit of the vortex flow sensor. The communicative coupling may be via wired or wireless data communication.

[0085] The processing circuit 16 may be configured to compute one or more of the following: the measured flow (e.g. the flow rate or flow speed) of the fluid passing through the flow channel 12 the viscosity of the fluid passing through the flow channel 12 an amount of a constituent of the fluid passing through the flow channel 12. The amount may e.g. be expressed as a concentration of the constituent. In some embodiments the constituent is an antifreeze agent such as glycol and the fluid is water, optionally including an antifreeze agent.

[0086] In some embodiments, the vortex flow sensor is configured to only compute, or at least to only output, one or two of the above quantities. In other embodiments, the vortex flow sensor is configured to compute and output all three of the above quantities. For example, in some embodiments, the vortex flow sensor only outputs the measured flow, in particular a viscosity-adjusted flow as described herein. In other embodiments, the vortex flow sensor is operable as a viscosity sensor and only outputs the viscosity of the fluid. Similarly, the vortex flow sensor may be operable as a concentration sensor only operable to output the computed centration of a constituent of the fluid. In yet further examples, the vortex flow sensor is operable to output the measured flow, in particular a viscosity-adjusted flow as described herein, and the viscosity and / or the amount of a constituent of the fluid, e.g. the amount of antifreeze agent, which may be expressed in terms of the level of freeze protection, or otherwise. The vortex flow sensor may be configured to compute one or more of the above quantities by performing the process of FIG. 3 and / or FIG. 10, or otherwise.

[0087] Example of a vortex flow sensor are described in more detail in EP 1434034 and in US 2009 / 0165565, the entire contents of which are hereby incorporated herein by reference.

[0088] Generally, such vortex flow sensors are particularly applied in conduit systems of circulations, be it in the conduit itself or also within the pump producing the circulation. Such a vortex flow sensor typically comprises a body projecting into the flow, the body being a so-called obstruction, and of a sensor arranged at a suitable distance therebehind, typically a pressure sensor, in particular a differential pressure sensor, or a deflection sensor measuring a deflection of a paddle or other deflecting member, or otherwise.

[0089] Vortex flow sensors may be manufactured in an inexpensive manner and may determine the measured flow with a high accuracy.

[0090] FIG. 3 schematically illustrates a block diagram of an embodiment of a process for determining the viscosity, glycol concentration and a measured flow of a fluid. The present example is based on measured sensor data from a vortex flow sensor, in particular sensor data representing measured pressure variations caused by vortex creation in a vortex flow sensor, e.g. as obtained by a vortex flow sensor as described above in connection with FIG. 2, or otherwise. It will be appreciated, however, that other sensor data indicative of the vortex creation may be used. The process may partly or completely be performed by a processing circuit integrated into a vortex flow sensor. Alternatively or additionally, the process may partly or completely be performed by one or more processing units external to the vortex flow sensor.

[0091] The process receives a time-series of measured sensor data, which represent a vortex signal indicative of the vortex formation in the vortex flow sensor, e.g. a magnitude of pressure variations due to vortex creation as a function of time. It will be appreciated that the process may include one or more initial signal processing steps such as filtering, analogue-to-digital conversion and / or the like.

[0092] In block 161, the process computes a measured flow from the received sensor data. The measured flow may be represented as a flow rate, a flow speed or as another suitable flow measurement value. This computation may be performed in a manner known in the art of vortex flow sensors, based on a proportionality of the vortex frequency to the flow speed, and related by the channel dimensions and the Strouhal number.

[0093] Additionally, in block 162, the process acquires the received sensor data. The process may acquire the data over a certain measurement period (e.g. 10 minutes or another suitable period). The process may represent the acquired sensor data as a vortex data set that includes acquired samples of the vortex signal. For example, the acquired vortex data set may include a predetermined number, e.g. 1500 or another suitable number, of signal samples. The process may divide the vortex data set into consecutive portions of a suitable size N, e.g. N=120 or another suitable size. The portions may or may not be overlapping. In some embodiments, the process may operate in a streaming or real-time mode, e.g. by continuously or intermittently forwarding the acquired sensor data to subsequent step 163, e.g. in real time or quasi real-time. Accordingly, the process may process the acquired sensor data in real-time or quasi-real-time without initially prerecording an entire vortex data set. In other embodiments, the process may be operated in a batch mode, e.g. by initially recording a vortex data set and then forwarding an entire recorded vortex data set to subsequent step 163.

[0094] In subsequent block 163, the process performs a feature extraction process for extracting one or more features from the received sensor data. In particular, the process extracts a standard deviation of the vortex frequency. Optionally, the process may extract one or more additional or alternative features, e.g. a mean vortex amplitude and / or the like.

[0095] In particular, for the purpose of extracting the standard deviation of the vortex frequency, the process may perform a transformation of respective portions of received signal samples into frequency space, e.g. by performing a fast Fourier transformation (FFT) of N signal samples, or otherwise. From the frequency representations, the process may derive a vortex frequency for each portion of signal samples, e.g. as a median or as a mean of the frequency distribution, or otherwise. The thus computed vortex frequencies from respective portions of signal samples form a distribution of vortex frequencies, from which the standard deviation of vortex frequencies can be computed. It will be appreciated that, in alternative embodiments, the process may compute another measure of dispersion of the vortex frequency or perform the computation in a different manner. The dispersion may be computed for a certain predetermined measurement period, e.g. a period of one or several minutes.

[0096] FIGs. 4A-C schematically illustrate the distribution of measured vortex frequencies of fluids having respective viscosities and flowing through a conduit at the same flow rate. In particular, each of FIGs. 4A-C schematically illustrate examples of frequency representations 401 of respective signal portions of a received vortex data set. Each curve 401 on the graphs represents the result of applying an FFT to a respective one of the portions of signal samples. FIG. 4A shows frequency representations of signal portions of a vortex data set for a fluid flow of a fluid having kinematic viscosity of 1 mm2 / s. FIGs. 4B and 4C show corresponding frequency representations for a fluid having kinematic viscosities of 4 mm2 / s and 10 mm2 / s, respectively. As illustrated by FIGs. 4A-C, the spread (STD) of flow vortex frequencies relates to the fluid's viscosity at a constant flow rate; specifically, a higher standard deviation is indicative of a higher viscosity.

[0097] Accordingly, again referring to FIG. 3, the correlation between the standard deviation of the vortex frequency and the viscosity of the fluid is exploited to compute an estimate of the viscosity of the fluid from the computed standard deviation. To this end, in block 164, the process may apply a predetermined regression model, e.g. a linear regression, that relates the observed standard deviation with the viscosity. The regression parameters of the regression model may be predetermined during a calibration process and based on reference measurements.

[0098] FIGs. 5A-D schematically illustrate an example of the relationship between the dispersion of measured vortex frequencies and the viscosity of a fluid. In each of FIGs. 5A-D, curve 501 shows measured STDs of the vortex frequencies as a function of viscosity where the viscosity was determined by a reference technique. In this example, as a reference technique, the glycol concentration was determined using a refractometer and the fluid temperature was determined using a temperature sensor. The reference kinematic viscosity was then determined from data sheets for the particular glycol employed. Curve 502 shows the difference between the maximum and minimum measured vortex frequencies as a function of the viscosity. All measurements of the vortex frequencies were performed by the same vortex flow sensor and at the same actual flow rate through the sensor (in this example at 10 l / min). All measurements were performed on water with added glycol. In FIG. 5A, the glycol concentration is 24.6%, in FIG.5B the glycol concentration is 27.4%, in FIG. 5C the glycol concentration is 29.2% and in FIG. 5D the glycol concentration is 38.2 %. 1

[0099] As can be seen from the figures, the standard deviation of the vortex frequency has a good linear correlation to the viscosity, independently of the glycol concentration. The difference between maximum and minimum vortex frequencies, as an alternative measure of dispersion of the vortex frequencies, also shows a certain degree of correlation, but here the correlation is not as good as for the STD.

[0100] Again referring to FIG. 3, in block 164, the process may further estimate the glycol concentration based on the determined viscosity. The computation of the glycol concentration may be based on known relationships between viscosity and glycol concentration. The known relationship may e.g. be established based on reference measurements or based on data sheets from respective antifreeze agents. As the relationship between glycol concentration and viscosity generally is temperaturedependent, the process may preferably receive a measured temperature of the fluid.

[0101] FIG. 6 schematically illustrates an example of the relationship between viscosity, glycol (in this example propylene glycol) concentration and temperature. Accordingly, from known values of the temperature and viscosity, the glycol concentration - or at least an estimate thereof - may be computed from the relationship shown in FIG. 6 or from a similar relationship applicable for the type of antifreeze agent used in the fluid system. To this end, the computed viscosity and the corresponding temperature data may be used to map out changes in viscosity over time. This means that multiple data sets of viscosity and temperature may be used to estimate the glycol concentration. As can be seen from FIG. 6, the viscosity for different glycol concentrations differs more at low temperature and becomes more similar at higher temperatures. By using a calculated viscosity value obtained at a low fluid temperature may thus provide a more accurate estimate of the glycol concentration. By obtaining multiple viscosity estimates at respective temperatures for a given fluid, a more accurate estimate of the glycol concentration may be obtained, e.g. by determining the best fit curve of a family of viscosity-temperature curves, or by using a difference between a calculated viscosity obtained for a low temperature minus the corresponding viscosity calculated for a high temperature. That way a possible bias of the viscosity calculation may be eliminated.

[0102] It will further be appreciated that the computation of an estimated glycol concentration may be performed directly from the measured vortex frequencies, i.e. without necessarily computing the viscosity. To this end, corresponding relationships between vortex frequency, glycol concentration and temperature may be mapped out and used to determine a glycol concentration from determined vortex frequencies and temperatures.

[0103] Yet further, from the thus estimated glycol concentration, the degree of freeze protection may be determined, e.g. from calibration experiments or agent-specific datasheets.

[0104] Again referring to FIG. 3, in optional block 165, the computed viscosity may be used to improve the measured flow value as determined in block 161. The correction of the measured flow value is based on the observation that a change in viscosity introduces an offset in the flow measurement, in particular for viscosities larger than 1 mm2 / s. Accordingly, compensating for this offset based on the determined viscosity may increase the accuracy of the flow measurement.

[0105] The relationship between measured flow, flow offset and viscosity is illustrated in FIG. 7, which schematically illustrates an example of the relationship between flow measurement errors and viscosity. In particular, FIG. 7 illustrates the relationship between flow offset and viscosity for different values of the flow speed. Curve 701 shows the relationship for a low flow speed, curve 702 shows the relationship for an intermediate flow speed, while curve 703 shows the relationship for a high flow speed. As illustrated in FIG. 7, the offset in the measured flow increases with the rise in viscosity. Additionally, the offset in the measured flow speed is more significant at low flow rates compared to high flow rates.

[0106] Again referring to FIG. 3, the compensation of the measured flow speed for the viscosity-dependent offset may thus be based on pre-established relationships between viscosity and offset for respective flow rates. For example, the computation of the applicable offset may be based on a suitable regression model established from reference measurements, e.g. as illustrated in FIGs. 8A-B.

[0107] Generally, the determination of the flow offset may be performed based on a model relating the flow offset to the viscosity and / or to the measure of dispersion. The model may be a predetermined model. The model may be a regressions model, a trained machine-learning model or another suitable model.

[0108] FIGs. 8A-B schematically illustrate an example of the correction of flow measurements based on measured viscosities. FIG. 8A shows an experimentally established linear regression model 801 established for a nominal flow rate of 10 l / min and for different viscosities as established by a reference method. Each dot in FIG. 8A represents the offset of a flow measurement by a vortex flow sensor relative to the nominal flow rate. In the example of FIG. 8A, measurements were performed with water-glycol mixtures at different concentrations of glycol. Curve 801 is a linear fit of the measured data. As can be seen from FIG. 8A, in this example, a linear regression model provides an adequately accurate regression model over a large range of viscosities. It will be appreciated that in other examples, non-linear regression models may be more appropriate. In some embodiments, respective regression models may be employed for different flow rate intervals, for different flow channels, and / or the like.

[0109] FIG. 8B illustrates an example of the performance of the resulting flow measurement process. Curves 811, 812 and 813 show the actual relative error of flow measurements at different viscosities compared to a nominal flow of 10 l / min. Curve 811 shows the flow offset of the raw flow measurement results from a vortex flow sensor, curve 812 shows the corresponding absolute fullscale error of the adjusted flow speed measurements, where the raw measurements were adjusted based on the calculated viscosity, calculated from the STD of the vortex frequencies as described in connection with FIG. 3, and based on the linear regression of FIG. 8A. Finally, curve 823 shows the corresponding error of the adjusted flow speed measurements, where the raw measurements were adjusted based on reference viscosity measurements and based on the linear regression of FIG. 8A.

[0110] As can be seen from FIG. 8B, the adjustment based on the viscosity calculation obtained from the observed standard deviations of the vortex frequencies in the vortex flow sensor results in a considerable improvement of the accuracy of the flow measurement. Moreover, the improvement is comparable with the improvement that can be obtained using a reference viscosity measurement. Accordingly, embodiments of the method described herein provides accurate flow measurements using merely a vortex flow sensor and without the need for any additional viscosity sensing equipment.

[0111] As was the case for the calculation of the glycol concentration, it will be appreciated that the adjustment of the flow measurement for a viscosity-dependent offset may alternatively be performed directly from the measured standard deviation of the vortex frequencies and from a corresponding regression model relating the STD of vortex frequencies with the flow offset. FIGs. 9A-C schematically illustrate another example of the relationship between the dispersion of measured vortex frequencies and the viscosity of a fluid. FIGs. 9A-C are similar to FIGs. 5A-D in that they each show a graph 501 of the STD of the vortex frequencies as a function of viscosity as determined by a reference technique, while graph 502 shows the difference between the maximum and minimum measured vortex frequencies as a function of the viscosity. In the examples of FIGs. 9A-C, all measurements were performed on water with added glycol at the same concentration, in this example 24.4%, but at different flow rates, namely 25 l / min., 35 l / min. and 45 l / min, respectively. Measurements were performed with the same vortex flow sensor as the measurements of FIGs. 5A-D. By comparing FIG. 5A with FIGs. 9A-C it can be seen that, with increasing flow rates, the linear correlation between viscosity and the observed dispersion of the vortex frequency measurements becomes worse. Accordingly, it some embodiments, it may be beneficial to perform the viscosity measurements described herein when the measured flow rates are relatively low, e.g. lower than a predetermined threshold, which may be experimentally be established for a particular model of vortex flow sensor and depend on the desired accuracy of the viscosity determination. During operation, the process may thus monitor the measured flow rate and perform a calculation of the viscosity when the measured flow rate is sufficiently low. If necessary, the process may control the fluid system to intermittently reduce the actual flow rate so as to enable accurate viscosity measurements.

[0112] FIG. 10 schematically illustrates a flow diagram of an embodiment of a process for determining a viscosity-related property of a fluid.

[0113] In step SI, the process monitors and / or controls one or more operational conditions associated with the fluid flow of the fluid, in particular the degree of flow and / or the fluid temperature. In embodiments, where the process controls one or more operational conditions associated with the fluid flow, the process may control a pump, a valve and / or other component of the fluid system. Alternatively or additionally, the process may receive information about the nominal / expected operational conditions of the fluid system, e.g. the nominal flow and / or fluid temperature. Yet alternatively, the process may monitor measured flow rates and / or temperatures.

[0114] In step S2, the process selects a measurement period responsive to the monitored and / or controlled one or more operational conditions fulfilling one or more predetermined criteria. For example, the process may select a measurement period where the operational conditions are stable (e.g. constant nominal flow and constant temperature) and wherein the (nominal or measured) flow is at a level where a reliable correlation between the dispersion of vortex frequencies and the viscosity or viscosity- related property to be determined has been pre-established (e.g. in the form of a regression model, a look-up table or otherwise).

[0115] In step S3, the process determines the viscosity and / or viscosity-related property by determining the measure of dispersion of vortex frequencies from the plurality of measured values obtained during the selected measurement period, e.g. by performing the process of FIG. 3 or otherwise.

[0116] It will be appreciated that a number of modifications may be made to the process and system described herein.

[0117] For example, in some embodiments, the process may control the fluid system to increase the fluid temperature (e.g. by forcing hot water production to e.g. 60°C in a heat pump system) to obtain a reference point of the viscosity, (e.g. a value below 2cSt in the example of FIG. 6) no matter what the glycol concentration is. This reference point gives the possibility to check that the measured vortex-amplitude and the standard deviation of the vortex frequency indeed corresponds to the expected viscosity at the elevated temperature.

[0118] In some embodiments, the process may further estimate, from the recorded sensor data, the lowest vortex frequency observed over temperature. This data may provide an indication of the lowest possible flow that can sustain a vortex street, i.e. vortex creation with sufficiently high vortex amplitude (the vortex amplitude decreases with decreasing flow and with increasing kinematic viscosity). This may add a useful data point for the minimum observed vortex frequency during cycling of the fluid system, e.g. of a heat pump. Such an additional data point may e.g. be useful when a heat pump cycles ON to meet heat demand after a long OFF period. Upon start of the ON cycle, the process may detect the onset of the vortex creation and compare this measurement with the pre- established relationship of the minimum frequency over temperature, so as to obtain a fast spot check to determine whether the latest estimation of glycol concentration is still feasible, since the initial media in the outdoor unit will have cooled.

[0119] In some embodiments, the process may receive and utilize pump data on power consumption and / or torque required to obtain a given flow measurement from the sensor. This provides data on the density of the fluid being pumped, which in turn can be used to improve the estimate of the glycol concentration.

[0120] In some embodiments, the vortex flow sensor and the pump may be communicatively coupled. The pump may thus be controlled to change the pump speed based on a sensor metric as to how "good" a flow reading it has obtained.

[0121] Some embodiments of the various aspects disclosed herein may be summarized as follows: Embodiment 1: A method for determining a viscosity, and / or a property correlated with the viscosity, of a fluid of a fluid system, the method comprising:

[0122] - using a vortex flow sensor to obtain a plurality of measured values, the measured values being indicative of a degree of flow of the fluid;

[0123] - determining, from the plurality of measured values, a measure of dispersion of the measured values;

[0124] - determining the viscosity, and / or the property correlated with the viscosity, of the fluid from the determined measure of dispersion.

[0125] Embodiment 2: The method according to embodiment 1, wherein the measured values are indicative of at least one feature of vortex formation caused by the vortex flow sensor.

[0126] Embodiment 3: The method according to embodiment 2, wherein the at least one feature includes a degree of vortex formation, in particular a frequency of vortex formation.

[0127] Embodiment 4: The method according to any of the preceding embodiments, wherein the measure of dispersion is indicative of a standard deviation of the plurality of measured values.

[0128] Embodiment 5: The method according to any one of the preceding embodiments, wherein obtaining the sensor data comprises obtaining the sensor data during a period of stable flow conditions, in particular at a constant flow and / or at a constant pump speed.

[0129] Embodiment 6: The method according to any one of the preceding embodiments, further comprising performing the determining of the viscosity, and / or the property correlated with the viscosity, of the fluid from the determined measure of dispersion conditioned on a current operational state of the fluid system, in particular conditioned on a current magnitude and / or stability of the measured flow.

[0130] Embodiment 7: The method according to any one of the preceding embodiments, comprising:

[0131] - monitoring and / or controlling one or more operational conditions associated with the fluid flow of the fluid, in particular the degree of flow and / or the fluid temperature,

[0132] - selecting a measurement period responsive to the monitored and / or controlled one or more operational conditions fulfilling one or more predetermined criteria; and wherein determining the measure of dispersion comprises determining the measure of dispersion from from the plurality of measured values obtained during the selected measurement period.

[0133] Embodiment 8: The method according to any one of the preceding embodiments, wherein determining the viscosity, and / or the property correlated with the viscosity, of the fluid from the determined measure of dispersion comprises using a regression model relating dispersion with viscosity, and / or with a property correlated with the viscosity.

[0134] Embodiment 9: The method according to embodiment 8, wherein the regression model is a linear regression model.

[0135] Embodiment 10: The method according to any one of the preceding embodiments, wherein the property correlated with the viscosity is an amount of a constituent of the fluid, the constituent affecting the viscosity of the fluid, and wherein determining the amount of the constituent comprises determining the amount from at least the determined dispersion and / or the determined viscosity, and optionally further from a temperature of the fluid.

[0136] Embodiment 11: The method according to embodiment 10, wherein the constituent of the fluid includes an antifreeze agent, in particular a glycol.

[0137] Embodiment 12: The method according to any one of the preceding embodiments, wherein the property correlated with the viscosity is a freezing point of the fluid, and wherein determining the freezing point comprises determining the freezing point from at least the determined dispersion and / or the determined viscosity, and optionally further from a temperature of the fluid.

[0138] Embodiment 13: The method according to any one of the preceding embodiments, further comprising performing a flow measurement using the measured values and further based on the determined dispersion, in particular by determining a flow offset from the determined dispersion.

[0139] Embodiment 14: The method according to embodiment 13, wherein performing the flow measurement comprises:

[0140] - determining, from the plurality of measured values, a flow measurement value;

[0141] - determining an adjusted flow measurement value from determined flow measurement value and from the determined dispersion, in particular by determining a flow offset from the determined dispersion.

[0142] Embodiment 15: A method of performing a flow measurement of a flowing fluid, the method comprising:

[0143] - using a vortex flow sensor to obtain a plurality of measured values;

[0144] - determining, from the plurality of measured values, a flow measurement value; - determining, from the plurality of measured values, a measure of dispersion of the measured values;

[0145] - determining an adjusted flow measurement value from determined flow measurement value and from the determined dispersion, in particular by determining a flow offset from the determined dispersion.

[0146] Embodiment 16: The method according to embodiment 14 or 15, comprising:

[0147] - determining the viscosity of the fluid from the determined measure of dispersion,

[0148] - determining the adjusted flow measurement value from the flow measurement value and from the determined viscosity, in particular by determining a flow offset from the determined viscosity.

[0149] Embodiment 17: A data processing system configured to perform the steps of the method according to any one of the preceding embodiments.

[0150] Embodiment 18: A computer program comprising program code configured to cause, when executed by a data processing system, the data processing system to perform the steps of the method according to any one of embodiments 1 through 15.

[0151] Embodiment 19: An apparatus comprising a vortex flow sensor and a data processing system as defined in embodiment 17, the data processing system being configured to receive the sensor data from the vortex flow sensor.

[0152] Embodiment 20: A fluid system comprising an apparatus as defined in embodiment 19.

[0153] Various embodiments of the method described herein may be computer-implemented. In particular, embodiments of the method may be implemented by means of hardware comprising several distinct elements, and / or at least in part by means of a suitably programmed data processing system. In the apparatus claims enumerating several means, several of these means can be embodied by one and the same element, component or item of hardware. The mere fact that certain measures are recited in mutually different dependent claims or described in different embodiments does not indicate that a combination of these measures cannot be used to advantage.

[0154] It should be emphasized that the term "comprises / comprising" when used in this specification is taken to specify the presence of stated features, elements, steps or components but does not preclude the presence or addition of one or more other features, elements, steps, components or groups thereof.

Claims

CLAIMS1. A method for determining a viscosity, and / or a property correlated with the viscosity, of a fluid of a fluid system, the method comprising:- using a vortex flow sensor to obtain a plurality of measured values, the measured values being indicative of a degree of flow of the fluid;- determining, from the plurality of measured values, a measure of dispersion of the measured values;- determining the viscosity, and / or the property correlated with the viscosity, of the fluid from the determined measure of dispersion.

2. The method according to claim 1, wherein the measured values are indicative of at least one feature of vortex formation caused by the vortex flow sensor, in particular a degree of vortex formation, such as a frequency of vortex formation.

3. The method according to claim 2, wherein the at least one feature includes a degree of vortex formation, in particular a frequency of vortex formation.

4. The method according to any of the preceding claims, wherein the measure of dispersion is indicative of a standard deviation of the plurality of measured values.

5. The method according to any one of the preceding claims, wherein obtaining the sensor data comprises obtaining the sensor data during a period of stable flow conditions, in particular at a constant flow and / or at a constant pump speed.

6. The method according to any one of the preceding claims, further comprising performing the determining of the viscosity, and / or the property correlated with the viscosity, of the fluid from the determined measure of dispersion conditioned on acurrent operational state of the fluid system, in particular conditioned on a current magnitude and / or stability of the measured flow.

7. The method according to any one of the preceding claims, comprising:- monitoring and / or controlling one or more operational conditions associated with the fluid flow of the fluid, in particular the degree of flow and / or the fluid temperature,- selecting a measurement period responsive to the monitored and / or controlled one or more operational conditions fulfilling one or more predetermined criteria; and wherein determining the measure of dispersion comprises determining the measure of dispersion from from the plurality of measured values obtained during the selected measurement period.

8. The method according to any one of the preceding claims, wherein determining the viscosity, and / or the property correlated with the viscosity, of the fluid from the determined measure of dispersion comprises using a regression model relating dispersion with viscosity, and / or with a property correlated with the viscosity.

9. The method according to claim 8, wherein the regression model is a linear regression model.

10. The method according to any one of the preceding claims, wherein the property correlated with the viscosity is an amount of a constituent of the fluid, in particular an antifreeze agent, the constituent affecting the viscosity of the fluid, and wherein determining the amount of the constituent comprises determining the amount from at least the determined dispersion and / or the determined viscosity, and optionally further from a temperature of the fluid.

11. The method according to claim 10, wherein the constituent of the fluid includes an antifreeze agent, in particular a glycol.

12. The method according to any one of the preceding claims, wherein the property correlated with the viscosity is a freezing point of the fluid, and wherein determining the freezing point comprises determining the freezing point from at least the determined dispersion and / or the determined viscosity, and optionally further from a temperature of the fluid.

13. The method according to any one of the preceding claims, further comprising performing a flow measurement using the measured values and further based on the determined dispersion, in particular by determining a flow offset from the determined dispersion.

14. The method according to claim 13, wherein performing the flow measurement comprises:- determining, from the plurality of measured values, a flow measurement value;- determining an adjusted flow measurement value from determined flow measurement value and from the determined dispersion, in particular by determining a flow offset from the determined dispersion.

15. A method of performing a flow measurement of a flowing fluid, the method comprising:- using a vortex flow sensor to obtain a plurality of measured values;- determining, from the plurality of measured values, a flow measurement value;- determining, from the plurality of measured values, a measure of dispersion of the measured values;- determining an adjusted flow measurement value, in particular a viscosity-adjusted flow measurement value, from determined flow measurement value and from the determined dispersion, in particular by determining a flow offset from the determined dispersion.

16. The method according to claim 14 or 15, comprising:- determining the viscosity of the fluid from the determined measure of dispersion,- determining the adjusted flow measurement value from the flow measurement value and from the determined viscosity, in particular by determining a flow offset from the determined viscosity.

17. A data processing system configured to perform the steps of the method according to any one of the preceding claims.

18. A computer program comprising program code configured to cause, when executed by a data processing system, the data processing system to perform the steps of the method according to any one of claims 1 through 15.

19. An apparatus comprising a vortex flow sensor and a data processing system as defined in claim 17, the data processing system being configured to receive the sensor data from the vortex flow sensor.

20. A fluid system comprising an apparatus as defined in claim 19.

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