Virtual traffic calculation device, virtual traffic calculation method, and virtual traffic calculation program

Abstract

There is provided a virtual flow calculation apparatus including: an environmental information storage unit that stores environmental information indicating an environment of a real space metered by a flow sensor; a physical property information storage unit that stores physical property information indicating the physical property of the fluid to be measured; a simulation unit that simulates a flow phenomenon of a multiphase flow in the fluid in a virtual space in which the real space is reproduced by using the environmental information and the physical property information; and a calculation unit that calculates a virtual flow rate, which is an estimate of an actual flow rate measured by the flow rate sensor, on the basis of a result of the simulation.

Description

Technical Field

[0001] The present invention relates to a virtual flow calculation device, a virtual flow calculation method and a virtual flow calculation program.

[0002] The contents of the following patent applications are incorporated herein by reference:

[0003] Patent application No. 2023-012036 filed in Japan on January 30, 2023

[0004] Patent application No. 2023-046057 filed in Japan on March 22, 2023 Background Art

[0005] Patent Document 1 discloses that "a flowmeter design support system is provided that can improve the measurement accuracy of a differential pressure flowmeter and can reduce the risk of a non-negligible error in flow indication values ​​caused in an actual machine during the design phase."

[0006] (List of citations)

[0007] (Patent Document)

[0008] (Patent Document 1) Japanese Patent Application Publication No. 2020-144662

[0009] (Patent Document 2) Japanese Patent Application Publication No. 2019-194424

[0010] (Patent Document 3) Japanese Patent Application Publication No. 2012-132797

[0011] (Patent Document 4) Patent Document 4: Japanese Patent Application Publication No. 2009-014726 Summary of the Invention

[0012] In a first aspect of the present invention, a virtual flow calculation device is provided. The virtual flow calculation device includes: an environmental information storage unit that stores environmental information indicating the environment of a real space measured by a flow sensor; a physical property information storage unit that stores physical property information indicating the physical properties of a fluid to be measured; a simulation unit that simulates the flow phenomenon of a multiphase flow in the fluid in a virtual space that reproduces the real space by using the environmental information and the physical property information; and a calculation unit that calculates a virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor based on the results of the simulation. The simulation unit can simulate at least one of the flow velocity at a portion of the flow sensor or the flow velocity distribution at a cross section of the flow sensor.

[0013] In the virtual flow calculation device, the flow sensor may be at least one of a Coriolis flowmeter, an ultrasonic flowmeter, an electromagnetic flowmeter, or a vortex flowmeter.

[0014] In any of the aforementioned virtual flow calculation devices, the flow sensor may be a Coriolis flow meter, and the calculation unit may estimate at least one of the density of the fluid or the fraction of the multiphase flow based on a resonant frequency of a flow tube. The calculation unit may estimate the fluid density based on the resonant frequency of the flow tube in a vacuum and the resonant frequency of the flow tube containing the fluid. Furthermore, the calculation unit may estimate the fraction of the multiphase flow based on the resonant frequency of the flow tube and the resonant frequency of the flow tube when the fluid is solely in a gas phase or solely in a liquid phase.

[0015] In any of the virtual flow calculation devices, the flow sensor may be a Coriolis flow meter, and the calculation unit may estimate the fraction of the multiphase flow based on a drive current to be applied to an oscillator to vibrate the flow tube. The calculation unit may estimate the fraction of the multiphase flow by using a data set indicating a correlation between the drive current to be applied to the oscillator and a bubble fraction in the liquid.

[0016] In any of the virtual flow rate calculation devices, the flow rate sensor may be an ultrasonic flow meter, and the calculation unit may estimate a distribution state of particles dispersed in the fluid based on a result of analyzing a received signal strength of ultrasonic waves for each frequency band.

[0017] In any of the virtual flow rate calculation devices described above, the flow rate sensor may be an ultrasonic flow meter, and the calculation unit may estimate the uneven distribution state of particles dispersed in the fluid based on a difference between received signal intensities of opposing ultrasonic waves. The calculation unit may estimate the uneven distribution state of particles dispersed in the fluid from the difference between received signal intensities of opposing ultrasonic waves by using a data set indicating a correlation between the difference in received signal intensities and the uneven distribution state of particles.

[0018] In any of the virtual flow rate calculation devices, the flow rate sensor may be an electromagnetic flow meter, and the calculation unit may estimate the amount of flow noise generated in an electrode based on an electromotive force effect of an electrical insulator dispersed in the fluid.

[0019] In any of the virtual flow calculation devices, the flow sensor may be an electromagnetic flow meter, and the calculation unit may estimate the fraction of the multiphase flow based on a result obtained by parametrically calculating a result of the simulation.

[0020] In any of the virtual flow calculation devices, the flow sensor may be a vortex flowmeter, and the calculation unit may estimate the fraction of the multiphase flow based on an amplitude strength of a voltage generated in a piezoelectric element.

[0021] In any of the virtual flow calculation devices, the flow sensor may be a vortex flowmeter, and the calculation unit may estimate the fraction of the multiphase flow based on noise generated in a piezoelectric element.

[0022] In any of the aforementioned virtual flow calculation devices, when the fluid is in a multiphase state of gas and liquid, the calculation unit may calculate a virtual flow rate for the gas phase alone based on the fraction of the multiphase flow. In any of the aforementioned virtual flow calculation devices, the simulation unit may perform a multiphase fluid simulation using the estimated fraction of the multiphase flow and calculate a flow velocity distribution within the pipeline. The calculation unit may calculate a virtual flow rate for the gas phase alone from the simulation results.

[0023] Any of the virtual flow rate calculation devices may further include a diagnosis unit configured to issue an alarm when a parameter estimated by the calculation unit does not satisfy a predetermined reference.

[0024] In any of the virtual flow rate calculation devices, the diagnostic unit may further issue an alarm when a difference between the actual flow rate and the virtual flow rate does not satisfy a predetermined reference. The diagnostic unit may issue an alarm when a difference between the actual flow rate and the virtual flow rate is equal to or greater than a threshold value.

[0025] In any of the virtual flow calculation devices, the simulation unit may use an analytical model selected according to at least one of a combination of phases in the multiphase flow or a flow pattern.

[0026] In any of the virtual flow calculation devices, the analytical model may be a continuous phase model or a dispersed phase model.

[0027] Any of the aforementioned virtual traffic calculation devices may be provided by a cloud server.

[0028] In a second aspect of the present invention, a virtual flow calculation method is provided. The virtual flow calculation method is executed by a computer and includes: storing environmental information indicating the environment of a real space measured by a flow sensor; storing physical property information indicating the physical properties of a fluid to be measured; simulating a flow phenomenon of a multiphase flow in the fluid in a virtual space that reproduces the real space by using the environmental information and the physical property information; and calculating a virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor based on the simulation results.

[0029] In a third aspect of the present invention, a virtual flow calculation program is provided. When executed by a computer, the program causes the computer to function as: an environmental information storage unit that stores environmental information indicating the environment of a real space measured by a flow sensor; a physical property information storage unit that stores physical property information indicating the physical properties of a fluid to be measured; a simulation unit that simulates flow phenomena of a multiphase flow in the fluid in a virtual space that reproduces the real space by using the environmental information and the physical property information; and a calculation unit that calculates a virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor based on the results of the simulation.

[0030] The above summary of the invention does not necessarily describe all the necessary features of the embodiments of the present invention. The present invention may also be a sub-combination of the above features. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 An example of a block diagram of the virtual flow rate calculation device 100 and the sensor module 10 according to the present embodiment is shown.

[0032] Figure 2 An example of a flowchart of a virtual flow rate calculation method executed by the virtual flow rate calculation device 100 according to the present embodiment is shown.

[0033] Figure 3 An example of a block diagram of a virtual flow calculation device 100 used as a virtual Coriolis flow meter is shown.

[0034] Figure 4 An example of a block diagram of a virtual flow rate calculation device 100 serving as a virtual ultrasonic flow meter is shown.

[0035] Figure 5 An example of a block diagram of a virtual flow rate calculation device 100 serving as a virtual electromagnetic flowmeter is shown.

[0036] Figure 6 An example of a block diagram of a virtual flow calculation device 100 used as a virtual vortex flowmeter is shown.

[0037] Figure 7 An example of a block diagram of a virtual flow rate calculation device 100 and a sensor module 10 according to a first modification is shown.

[0038] Figure 8 An example of a block diagram of a virtual flow rate calculation device 100 and a sensor module 10 according to a second modification is shown.

[0039] Figure 9 An example of a flow pattern for a multiphase flow is shown.

[0040] Figure 10An example of a block diagram of the virtual flow rate calculation device 100 according to the second embodiment, which functions as a virtual Coriolis flowmeter, is shown.

[0041] Figure 11 An example of a block diagram of the virtual flow rate calculation device 100 according to the second embodiment, which functions as a virtual ultrasonic flow meter, is shown.

[0042] Figure 12 An example of a block diagram of a virtual flow rate calculation device 100 according to the second embodiment serving as a virtual electromagnetic flow meter is shown.

[0043] Figure 13 An example of a block diagram of the virtual flow rate calculation device 100 according to the second embodiment, which functions as a virtual vortex flowmeter, is shown.

[0044] Figure 14 An example of a computer 9900 is shown in which aspects of the present invention may be embodied in whole or in part. DETAILED DESCRIPTION

[0045] Hereinafter, the present invention will be described by way of embodiments of the invention, but the following embodiments do not limit the invention according to the claims. In addition, not all combinations of features described in the embodiments are essential to the solution of the invention.

[0046] Figure 1 An example block diagram of a virtual flow calculation device 100 and a sensor module 10 according to this embodiment is shown. Note that these blocks are functionally divided functional blocks and may not necessarily correspond to the actual device configuration. In other words, in this diagram, a unit shown as a single block does not necessarily consist of a single device. Furthermore, in this diagram, a unit shown as a separate block does not necessarily consist of a separate device. This also applies to subsequent block diagrams.

[0047] The sensor module 10 is set at various positions of the equipment, measures the physical quantity to be measured, and transmits the measured data to other devices. For example, such a device can be a device (group) for manufacturing products from raw materials. As an example, the device can be a factory. In addition to industrial factories such as chemical and biological factories, examples of factories can also include factories for managing and controlling wells such as gas fields and oil fields and their surroundings, factories for managing and controlling hydropower, thermal power and nuclear power generation, factories for managing and controlling environmental power generation such as solar energy and wind energy, factories for managing and controlling water supply and sewage, dams, etc. The sensor module 10 includes a flow sensor 20, a processing unit 30 and a sensor side communication unit 40.

[0048] The flow sensor 20 is a measuring instrument that measures the amount of a fluid (liquid, gas, steam, particulate matter, or a multiphase state thereof) flowing through the pipeline per unit time in a real space (e.g., a factory pipeline). Examples of such flow sensors 20 include various flowmeters employing different sensing principles depending on various conditions (e.g., the purpose of measurement, the measurement location, the type of fluid, or the state of the fluid). For example, the flow sensor 20 may be at least one of a Coriolis flowmeter, an ultrasonic flowmeter, an electromagnetic flowmeter, or a vortex flowmeter.

[0049] A Coriolis flowmeter utilizes the physical phenomenon of the Coriolis force. When fluid passes through a flow tube operating at a resonant frequency, the tube twists due to inertia, causing a phase shift in the detection signals from vibration detection sensors attached to the inflow and outflow sides of the flow tube. The Coriolis flowmeter detects this phase shift and multiplies it by a coefficient, for example, to output the flow rate.

[0050] An ultrasonic flowmeter utilizes the difference in ultrasonic propagation time. When ultrasonic waves are alternately transmitted and received while obliquely intersecting the fluid within a pipeline, they propagate slowly against the flow and rapidly within the fluid. Ultrasonic flowmeters calculate the flow velocity using the difference between the propagation times of the two ultrasonic waves, correct it to the average velocity at the surface using a flow correction factor, and then multiply this value by the cross-sectional area of ​​the pipeline to output the flow rate.

[0051] An electromagnetic flowmeter utilizes Faraday's electromagnetic induction. When an electromagnet generates a magnetic field and a conductive fluid passes through it, an electromotive force (EMF) proportional to the flow velocity is generated in a direction perpendicular to both the magnetic field and the fluid flow. Electromagnetic flowmeters detect the magnitude of this EMF and multiply it by the cross-sectional area of ​​the pipe, for example, to output the flow rate.

[0052] A vortex flowmeter utilizes Karman vortexes. When a columnar obstruction (vortex generator) is present in a flowing fluid, Karman vortices are generated downstream of the fluid. The flow velocity and the vortex frequency of the Karman vortices are proportional. In a vortex flowmeter, for example, the flow velocity is calculated using the vortex frequency of the Karman vortices. This frequency is then multiplied by the cross-sectional area of ​​the pipe to output the flow rate.

[0053] The flow sensor 20 may be, for example, at least one of the aforementioned Coriolis flowmeter, ultrasonic flowmeter, electromagnetic flowmeter, or vortex flowmeter. Note that the sensor module 10 may further include other sensors (not shown) capable of measuring physical quantities different from those of the flow sensor 20. For example, the sensor module 10 may further include other sensors such as a pressure gauge, a thermometer, a viscometer, a pH meter, a conductivity meter, or a slurry concentration meter.

[0054] The processing unit 30 performs signal processing on the output signals from the flow sensor 20 and other sensors. The processing unit 30 can supply measurement data obtained by performing signal processing on the output signals from the sensors to the sensor-side communication unit 40. Such measurement data can be data indicating at least the actual flow rate measured by the flow sensor 20.

[0055] The sensor-side communication unit 40 includes a communication stack (including a data link layer and an application layer) and a communication driver (including a physical layer) for communicating with the virtual flow rate calculation device 100 according to a communication protocol. The sensor-side communication unit 40 can transmit the measurement data supplied from the processing unit 30 to the virtual flow rate calculation device 100 via the network.

[0056] Typically, the flow sensor 20 is calibrated under reference operating conditions in equipment traceable to national standards. For example, the reference operating conditions are: fluid = water, fluid temperature = room temperature ±α, ambient temperature = room temperature ±α, and upstream / downstream straight pipe length = sufficient length. When such a flow sensor 20 is used for measurement in real space, operating conditions (such as fluid type, fluid temperature, ambient temperature, or upstream / downstream straight pipe length) differ from the reference operating conditions during calibration, resulting in discrepancies with the calibrated values.

[0057] Naturally, the supplier of the flow sensor 20 assumes these variations in operating conditions and designs the sensor to minimize the effects of the operating environment and fluid properties. However, if instrument changes due to long-term use or changes in actual flow equipment occur, it will be necessary to estimate the actual flow rate based on fluctuations in the flow sensor 20's output measured in real space and internal state information. Furthermore, to ensure the integrity of the flow sensor 20, it is necessary to perform a final recalibration using equipment traceable to national standards.

[0058] In this regard, the virtual flow rate calculation device 100 according to this embodiment performs a simulation related to fluid measurement in a virtual space, assuming the usage conditions of the flow rate sensor 20 measuring in a real space, such as the usage environment and fluid physical properties, and calculates a virtual flow rate, which is an estimate of the actual flow rate, based on the simulation results. The virtual flow rate calculation device 100 according to this embodiment includes an environmental information storage unit 110, a physical property information storage unit 120, a device-side communication unit 130, a simulation unit 140, a calculation unit 150, and a diagnostic unit 160.

[0059] The environment information storage unit 110 stores environment information indicating the environment of the real space measured by the flow sensor 20. For example, the environment information storage unit 110 may be a database and may store environment information acquired via user input, various storage devices, a network, etc., so that it can be accessed from the computing unit 150.

[0060] The physical property information storage unit 120 stores physical property information indicating the physical properties of the fluid to be measured. For example, the physical property information storage unit 120 may be a database and may store physical property information obtained via user input, various storage devices, a network, etc., so that it can be accessed from the computing unit 150 .

[0061] The device-side communication unit 130 includes a communication stack and a communication driver for communicating with the sensor module 10 according to a communication protocol. For example, the device-side communication unit 130 can communicate with the sensor module 10 via a network and acquire measurement data from the sensor module 10. As described above, such measurement data may be data indicating at least the actual flow rate measured by the flow sensor 20. The device-side communication unit 130 can supply the acquired measurement data to the diagnostic unit 160.

[0062] The simulation unit 140 uses the environmental information and physical property information to perform simulations related to fluid measurement in a virtual space that replicates the real space. For example, the simulation unit 140 may perform simulations related to fluid measurement in the virtual space based on instructions from the calculation unit 150 by using the environmental information stored in the environmental information storage unit 110 and the physical property information stored in the physical property information storage unit 120. The simulation unit 140 may supply the simulation results to the calculation unit 150.

[0063] The calculation unit 150 calculates a virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor 20 based on the simulation result. For example, the calculation unit 150 may obtain the simulation result from the simulation unit 140 and calculate the virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor 20 based on the simulation result. The calculation unit 150 may notify the diagnosis unit 160 of the calculated virtual flow rate.

[0064] The diagnosis unit 160 diagnoses the flow sensor 20 based on the actual flow rate and the virtual flow rate. For example, the diagnosis unit 160 may compare the actual flow rate indicated by the measurement data supplied from the device-side communication unit 130 with the virtual flow rate notified from the calculation unit 150 to diagnose the flow sensor 20.

[0065] The virtual flow calculation device 100 including such a functional unit can be a computer such as a personal computer (PC), a tablet computer, a smart phone, a workstation, a server computer, or a general-purpose computer, or can be a computer system in which multiple computers are connected. Such a computer system is also a computer in a broad sense. In addition, the virtual flow calculation device 100 can be implemented by one or more virtual computer environments that can be executed within a computer. Alternatively, the virtual flow calculation device 100 can be a dedicated computer designed for calculating virtual flow, or can be dedicated hardware implemented by dedicated circuits. In addition, when it can be connected to the Internet, the virtual flow calculation device 100 can be implemented through cloud computing. In particular, from the perspective of processing power and storage capacity, the virtual flow calculation device 100 is preferably provided by a cloud server.

[0066] Furthermore, such a computer may include a memory storing a virtual flow calculation program and a processor executing the virtual flow calculation program, and the functions of the virtual flow calculation device 100 may be realized by the processor executing the virtual flow calculation program. Specifically, a virtual flow calculation program may be provided that, when executed by a computer, causes the computer to function as: an environmental information storage unit 110 storing environmental information indicating the environment of the real space being measured by the flow sensor 20; a physical property information storage unit 120 storing physical property information indicating the physical properties of the fluid to be measured; a simulation unit 140 performing a simulation related to fluid measurement in a virtual space that reproduces the real space using the environmental information and the physical property information; and a calculation unit 150 calculating a virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor 20 based on the results of the simulation.

[0067] Figure 2 This figure shows an example of a flowchart of a virtual flow rate calculation method executed by the virtual flow rate calculation device 100 according to this embodiment. Each step in the virtual flow rate calculation method can be executed by a computer as the main operator. However, in each step, it is sufficient that the computer as a whole is the main operator, and it is also possible to include a case where a part other than the computer executes a part as a non-essential part.

[0068] In step S210, the computer stores environmental information. For example, the environmental information storage unit 110 may store environmental information indicating the environment of the real space measured by the flow sensor 20, thereby being accessible from the computing unit 150. At this time, as an example, the environmental information storage unit 110 may store information about the pipe attached to the outside of the flow sensor 20 (straight pipe length, state of the upstream / downstream bend pipe, etc.), information about the attached gasket, information about the fluid (liquid type, concentration, presence or absence of a mixed phase, assumed temperature, assumed pressure, etc.), information about peripheral equipment, etc. as environmental information. Note that a portion of such environmental information, such as pipe information, may be extracted from computer-aided design (CAD) data, aerial photography data, etc.

[0069] Here, when the usage environment changes over time, the environmental information storage unit 110 can store measurement data from other sensors similar to the flow sensor 20 (such as a pressure gauge, thermometer, viscometer, pH meter, conductivity meter, or slurry concentration meter) in real space as environmental information. Furthermore, the environmental information storage unit 110 can store the measurement data of the flow sensor 20, that is, the actual flow rate measured by the flow sensor 20 itself, as environmental information. In this case, the environmental information storage unit 110 can store the measurement data in a time series, assuming that the data changes over time.

[0070] In step S220, the computer stores physical property information. For example, the physical property information storage unit 120 can store physical property information indicating the physical properties of the fluid to be measured, so that it can be accessed from the calculation unit 150. At this time, as an example, the physical property information storage unit 120 can store information such as density, viscosity, conductivity, resistivity, dielectric constant or acoustic characteristics as physical property information, including temperature and pressure characteristics of the fluid to be measured. In addition, in the above description, the case where the physical property information storage unit 120 only stores physical property information indicating the physical properties of the fluid to be measured is described as an example, but the present invention is not limited to this. In addition to the fluid to be measured, the physical property information storage unit 120 can also store physical property information indicating the physical properties of various substances required for simulation. At this time, the physical property information storage unit 120 can store various types of information recorded in the so-called science chronology or various basic physical property databases (for example, the temperature characteristics of the resistivity and mechanical properties of metals) as physical property information.

[0071] In step S230, the computer acquires measurement data. For example, the device-side communication unit 130 may acquire measurement data from the sensor module 10 via the network. As described above, such measurement data may be data indicating at least the actual flow rate measured by the flow sensor 20.

[0072] At this time, the environmental information storage unit 110 may update the environmental information stored in step S210 by adding the acquired measurement data (measurement data of the flow sensor 20 or measurement data of other sensors) in time series.

[0073] In step S240, the computer performs the simulation. For example, the computing unit 150 may access the environmental information storage unit 110 to obtain the environmental information required for the simulation. In addition, the computing unit 150 may access the physical property information storage unit 120 to obtain the physical property information required for the simulation. Note that, as described above, such physical property information may include information indicating the physical properties of the fluid to be measured, or may include information indicating the physical properties of substances other than the fluid to be measured. The computing unit 150 may then supply this information to the simulation unit 140 and instruct it to perform the simulation. In response to this, the simulation unit 140 may perform a simulation related to the measurement of the fluid in a virtual space that reproduces the real space, for example, on a digital twin, by using the environmental information and the physical property information.

[0074] For example, the simulation unit 140 may perform simulation using a known numerical analysis method such as the finite element method (FEM) or the finite difference method (FDM). In this case, the simulation unit 140 may simulate at least one of stress, fluid, electromagnetic field, or ultrasonic wave in a virtual space.

[0075] For example, in stress simulation, the simulation unit 140 can simulate the vibration state applied to the flow sensor 20 through the pipeline from a vibration source such as a pump. In addition, the simulation unit 140 can simulate the fluid pressure applied to the flow sensor 20 based on information from a pressure gauge, a liquid level gauge, etc. In addition, the simulation unit 140 can simulate the stress distribution to the pipeline caused by bolt tightening, stamping, etc. between the pipelines.

[0076] Furthermore, for example, in a fluid simulation, the simulation unit 140 can input basic information such as pump lift, fluid flow, and pressure loss from the entire piping system to simulate the flow rate of the flow meter section used in real space. In this case, by performing the fluid simulation in the entire model, the actual flow rate can be directly compared with the virtual flow rate. The advantage here is that the flow velocity distribution in the flow meter cross-section, which varies with the flow velocity and fluid viscosity, can be known. Coriolis flowmeters, ultrasonic flowmeters, electromagnetic flowmeters, and vortex flowmeters are easily affected by the flow velocity distribution, but it is possible to estimate whether their output depends on the flow velocity distribution. On the other hand, when assuming a fluid simulation of the piping of an entire facility (such as a factory) is difficult to perform due to the performance of the computing device, the simulation unit 140 can omit some elements to perform the simulation. In this case, a deviation may occur between the actual flow rate and the virtual flow rate. Therefore, in this case, the simulation unit 140 can set the set point flow rate set by the proportional-integral-derivative (PID) control on the control system used in the factory, etc. as the initial value, or can set the actual flow value during a period considered to be normal operation as the initial value. The simulation unit 140 can reduce the calculation load by partially performing the fluid simulation, but in this case, a difference between the value of the virtual flow rate regarded as a normal operation state and the value of the actual flow rate is observed.

[0077] Furthermore, for example, in the electromagnetic field simulation, the simulation unit 140 may give applied current values ​​of two coils provided in the flow sensor 20 as initial values ​​and simulate the magnetic flux density distribution at the cross section of the pipeline.

[0078] In addition, for example, in ultrasonic propagation simulation, the simulation unit 140 can simulate ultrasonic propagation time, ultrasonic signal attenuation, etc. according to fluid properties, factory pipeline parameters, and ambient temperature.

[0079] As described above, the simulation unit 140 may simulate at least one of stress, fluid, electromagnetic field, or ultrasonic wave in a virtual space, and preferably a combination thereof.

[0080] In step S250, the computer calculates the virtual flow rate. For example, the calculation unit 150 can calculate the virtual flow rate as an estimate of the actual flow rate measured by the flow rate sensor 20 based on the simulation results in step S240. Usually, the flow rate distribution and fluid properties (pressure, density, viscosity, etc. of the fluid) vary according to pipeline conditions, fluid conditions, etc. However, the calculation unit 150 calculates the virtual flow rate based on the simulation results of the usage environment information and physical property information. Therefore, the calculation unit 150 can reflect the actual usage environment and fluid properties in the calculation, thereby calculating a virtual flow rate that is a more accurate estimate of the actual flow rate. The specific calculation of the virtual flow rate will be described in detail later with respect to the respective sensing principles of the flow meter.

[0081] The calculation unit 150 can determine the process for calculating the virtual flow rate based on the actual flow rate and the virtual flow rate during a period when the flow sensor 20 is deemed to be operating normally. More specifically, when the flow sensor 20 is measuring in a real space and there is a difference between the virtual flow rate calculated during a period when operation is deemed normal and the actual flow rate, the calculation unit 150 can multiply the virtual flow rate calculated as a correction value by a ratio corresponding to the difference and use the result as the initial result of the virtual flow rate. Therefore, for example, even when the flow sensor 20 includes time-dependent errors, by matching the calculation result of the virtual flow rate with the actual flow rate in an initial stage that does not include time-dependent errors, such as immediately after the flow sensor 20 is attached to the real space, the virtual flow meter can be calibrated with an initial value of the correct flow rate (a flow rate closer to the actual flow rate that does not include time-dependent errors). Furthermore, by adding calculation conditions for the virtual flow rate (for example, using measurement data in the real space as ambient temperature or setting the convergence value of the simulation to a smaller value), the calculation unit 150 can make the virtual flow rate closer to the actual flow rate through repeated calculations. In addition, when calculating a virtual flow rate based on the results of fluid simulation, the calculation unit 150 can calculate the virtual flow rate based on the results of fluid simulation with actual flow rate, and calculate a virtual flow rate that is closer to the actual flow rate by repeating the process of calculating the virtual flow rate using fluid simulation with a value closer to the actual flow rate.

[0082] In step S260 , the computer compares the actual flow rate with the virtual flow rate. For example, the diagnosis unit 160 may compare the actual flow rate indicated by the measurement data acquired in step S230 with the virtual flow rate calculated in step S250 .

[0083] In step S270, the computer determines whether the difference satisfies a criterion. For example, as a result of the comparison in step S260, the diagnostic unit 160 may determine whether the difference between the actual flow rate and the virtual flow rate satisfies a predetermined criterion. If the difference satisfies the criterion (Yes) (e.g., the difference is less than a threshold), the virtual flow rate calculation device 100 may return the process to step S230 and continue the flow. On the other hand, if the difference does not satisfies the criterion (No) (e.g., the difference is greater than or equal to the threshold), the virtual flow rate calculation device 100 may proceed to step S280.

[0084] In step S280, the computer issues an alarm. For example, the diagnostic unit 160 may output a message indicating that the difference does not meet a criterion to be displayed on a monitor, may output the message as a voice message, may print the message, or may send a signal. For example, in this manner, the diagnostic unit 160 may issue an alarm when the difference between the actual flow rate and the virtual flow rate does not meet a predetermined criterion. Thus, the diagnostic unit 160 can diagnose the flow sensor 20 based on the actual flow rate and the virtual flow rate.

[0085] The virtual flow calculation device 100 then terminates the process. Note that the virtual flow calculation device 100 can dynamically perform these calculations and diagnoses. For example, the virtual flow calculation device 100 can continuously calculate the virtual flow rate and diagnose the flow sensor 20 at a period that is a multiple of the actual flow measurement period. Furthermore, the virtual flow calculation device 100 can calculate the virtual flow rate and diagnose the flow sensor 20 at user-specified times (e.g., hourly, daily, or based on events such as the start of operation, etc.). Furthermore, the virtual flow calculation device 100 can calculate the virtual flow rate and diagnose the flow sensor 20 when the actual flow rate fluctuates to a value specified by the user or the system (e.g., 5% of the measurement span), when the conditions input to the environmental information or physical property information change, or when the change exceeds a user-specified value (e.g., 5%).

[0086] As explained using this flow, a virtual flow rate calculation method executed by a computer can be provided, comprising: storing environmental information indicating the environment of the real space measured by the flow sensor 20; storing physical property information indicating the physical properties of the fluid to be measured; performing a simulation related to the measurement of the fluid in a virtual space that reproduces the real space by using the environmental information and the physical property information; and calculating a virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor 20 based on the simulation results. Therefore, the specific calculation of the virtual flow rate will be explained in detail for each type of flow meter.

[0087] Figure 3 An example of a block diagram of a virtual flow rate calculation device 100 used as a virtual Coriolis flowmeter is shown. The virtual flow rate calculation device 100 can function as a virtual Coriolis flowmeter. When used as a virtual Coriolis flowmeter, the simulation unit 140 may include, for example, a fluid simulation unit 141, a stress simulation unit 142, and an electromagnetic field simulation unit 143. The virtual flow rate calculation device 100 can then estimate the output value of a Coriolis flowmeter to be used in real space by using, for example, the fluid simulation unit 141, the stress simulation unit 142, and the electromagnetic field simulation unit 143.

[0088] More specifically, when a coefficient as a function of structural feature quantities (such as the shape of the flow tube and the position of the vibration detection sensor) is represented by SK, and a phase time difference calculated from the phase difference between the vibrations generated on the upstream and downstream sides of the flow tube is represented by τ, the calculation unit 150 can calculate the virtual flow rate Q by the following equation. That is, the calculation unit 150 can calculate the virtual flow rate Q by multiplying the coefficient SK and the phase time difference τ. Here, the phase time difference τ is obtained by multiplying the phase difference generated in the vibration detection sensor by It is obtained by dividing by the excitation frequency fr of the oscillator. Therefore, the virtual flow Q can also be expressed as the coefficient SK and the phase difference The product of divided by the excitation frequency fr.

[0089] (Mathematical formula 1)

[0090]

[0091] Simulation unit 140 can perform stress simulation on coefficient SK using stress simulation unit 142. For example, stress simulation unit 142 can output the flow tube shape of a virtual Coriolis flowmeter using a 3D model of the flow tube, oscillator, and vibration detection sensor at normal temperature and pressure, along with temperature and pressure obtained from a meter in real space, as input. Furthermore, stress simulation unit 142 can output the resonant frequency or moment of inertia of the flow tube required to calculate coefficient SK using the same flow tube shape and Young's modulus under the same conditions as input.

[0092] The calculation unit 150 can then calculate the coefficient SK by calculating characteristic quantities such as the natural angular frequency from the results of the stress simulation (where, as described above, the temperature and pressure applied to the flow tube are added to the excitation force of the oscillator that drives the flow tube vibration) and substituting the calculated characteristic quantities into a function having the pre-derived characteristic quantities as variables.

[0093] In addition, regarding the phase time difference τ, the simulation unit 140 may perform coupled simulation by using the fluid simulation unit 141, the stress simulation unit 142, and the electromagnetic field simulation unit 143. Then, the calculation unit 150 may calculate the phase difference generated in the vibration detection sensor from the result of the coupled simulation. And the phase difference The phase time difference τ is calculated by dividing it by the excitation frequency fr of the oscillator.

[0094] Figure 4An example of a block diagram of a virtual flow rate calculation device 100 used as a virtual ultrasonic flow meter is shown. The virtual flow rate calculation device 100 can function as a virtual ultrasonic flow meter. When used as a virtual ultrasonic flow meter, the simulation unit 140 may include, for example, a fluid simulation unit 141 and an ultrasonic wave propagation simulation unit 144. The virtual flow rate calculation device 100 can then estimate the output value of an ultrasonic flow meter to be used in a real space by using, for example, the fluid simulation unit 141 and the ultrasonic wave propagation simulation unit 144.

[0095] More specifically, when the angle between the measuring tube axis and the ultrasonic wave propagation axis is represented by θ, the distance over which the ultrasonic wave propagates is represented by L, the propagation time for the ultrasonic wave to propagate from the upstream side to the downstream side is represented by t1, and the propagation time for the ultrasonic wave to propagate from the downstream side to the upstream side is represented by t2, the calculation unit 150 can calculate the flow velocity v by the following equation. That is, the calculation unit 150 can calculate the flow velocity v by using a function of the inverse difference (frequency difference) of the propagation time.

[0096] (Mathematical formula 2)

[0097]

[0098] Then, when the flow rate correction coefficient is represented by k and the cross-sectional area of ​​the pipeline is represented by A, the calculation unit 150 can calculate the virtual flow rate Q by the following formula. That is, the calculation unit 150 can calculate the virtual flow rate by correcting the flow rate v to the average flow rate at the cross-section through which the fluid flows using the flow rate correction coefficient k, and then multiplying the average flow rate by the cross-sectional area A of the pipeline.

[0099] (Mathematical formula 3)

[0100]

[0101] At this time, regarding the propagation times t1 and t2, the simulation unit 140 can perform fluid simulation using the fluid simulation unit 141. As an example, the fluid simulation unit 141 can calculate the three-dimensional flow velocity distribution within the measurement pipe by taking into account upstream / downstream straight pipe lengths, upstream / downstream flow bends, fluid viscosity, etc. At this time, the actual flow rate (flow velocity) output value of the flow sensor 20 measured in real space can be used as needed.

[0102] Furthermore, the simulation unit 140 can perform an ultrasonic wave propagation simulation using the ultrasonic wave propagation simulation unit 144. For example, for ultrasonic waves emitted from a piezoelectric element, when the flow rate is zero, the ultrasonic wave propagation simulation unit 144 can calculate the propagation time from upstream to downstream and from downstream to upstream at upstream and downstream sensor attachment locations. The ultrasonic wave propagation simulation unit 144 can then calculate the propagation time by taking into account pipeline parameters such as pipe wall thickness and dimensions, and temperature (ambient temperature and fluid temperature), thereby simulating the propagation of the ultrasonic wave.

[0103] The calculation unit 150 can then calculate the propagation time t1 from the upstream side to the downstream side and the propagation time t2 from the downstream side to the upstream side by coupling analysis using the three-dimensional flow velocity distribution within the measurement pipe and the propagation time based on the simulation result of ultrasonic propagation. Through the coupling analysis, the propagation times t1 and t2 can be calculated by combining the propagation time calculated by the ultrasonic propagation simulation with the three-dimensional flow velocity distribution calculated by the fluid simulation.

[0104] Figure 5 An example block diagram of a virtual flow rate calculation device 100 used as a virtual electromagnetic flowmeter is shown. The virtual flow rate calculation device 100 can function as a virtual electromagnetic flowmeter. When used as a virtual electromagnetic flowmeter, the simulation unit 140 may include, for example, a fluid simulation unit 141 and an electromagnetic field simulation unit 143. The virtual flow rate calculation device 100 can then estimate the output value of an electromagnetic flowmeter to be used in real space by using, for example, the fluid simulation unit 141 and the electromagnetic field simulation unit 143.

[0105] More specifically, the calculation unit 150 may calculate the electromotive force e generated in the electrode by the following equation: That is, the calculation unit 150 may calculate the electromotive force e by multiplying and integrating the weight function w, the magnetic flux density B, and the flow velocity v.

[0106] (Mathematical formula 4)

[0107] e=∫(w·B·v)ds

[0108] Then, the calculation unit 150 may calculate the virtual flow rate Q by the following equation. That is, the calculation unit 150 may calculate the virtual flow rate Q by using the calculated electromotive force e, the pipe inner diameter D, and the constant K.

[0109] (Mathematical formula 5)

[0110]

[0111] Here, regarding the magnetic flux density B, the simulation unit 140 can perform an electromagnetic field simulation using the electromagnetic field simulation unit 143. As an example, the electromagnetic field simulation unit 143 can calculate the magnetic flux density distribution within the measurement pipe by inputting the dimensions of the coil and magnetic material of the electromagnetic flowmeter and the physical property values ​​of the magnetic material. At this time, for the magnetic flux density, the measured magnetic flux density distribution within the measurement pipe can be stored as a database. This method can be used when there is no design information such as the product of another company (at least one of the dimensions of the coil and magnetic material of the product of the other company or the physical property values ​​of the magnetic material).

[0112] Furthermore, regarding the flow velocity v, the simulation unit 140 can perform fluid simulation using the fluid simulation unit 141. For example, the fluid simulation unit 141 can calculate the flow velocity distribution at the cross section of the measurement pipeline by taking into account upstream / downstream straight pipe lengths, upstream / downstream flow bends, fluid viscosity, etc. In this case, the actual flow rate (flow velocity) output value of the flow sensor 20 measured in real space can be used as needed.

[0113] The weight function w is a function of the electric field (magnetic flux density × flow velocity) generated at each point in the measurement pipeline and the distance between the electrodes. For example, the weight function described in JIS B 7554 or a weight function based on the electrode shape or configuration position can be used.

[0114] The calculation unit 150 then calculates the electromotive force e generated in the electrode by multiplying the electric field (magnetic flux density B x flow velocity v) generated at each point in the measurement pipeline by the weighting function w and integrating the result. In this case, since material properties may have a certain range, the calculated electromotive force e may be multiplied by a certain coefficient.

[0115] Figure 6 An example of a block diagram of a virtual flow calculation device 100 used as a virtual vortex flowmeter is shown. The virtual flow calculation device 100 can function as a virtual vortex flowmeter. When used as a virtual vortex flowmeter, the simulation unit 140 may include, for example, a fluid simulation unit 141. The virtual flow calculation device 100 can then estimate the output value of a vortex flowmeter to be used in a real space by using, for example, the fluid simulation unit 141.

[0116] More specifically, the calculation unit 150 can calculate the virtual flow rate Q using the following formula. That is, the calculation unit 150 can calculate the virtual flow rate Q by multiplying the vortex frequency f by the pipe cross-sectional area A and the width d of the vortex generator, and dividing the result by the Strouhal number St. Note that the Strouhal number St is a dimensionless number determined by the shape and size of the vortex generator.

[0117] (Mathematical formula 6)

[0118]

[0119] Regarding the vortex frequency f, simulation unit 140 can perform fluid simulation using fluid simulation unit 141. For example, fluid simulation unit 141 can input the physical properties of the fluid, the shape of the vortex bar, and pipeline conditions (straight pipe length, step difference, etc.) to simulate the generation of vortices within the measurement pipeline. In this case, the actual flow rate (flow velocity) output value of flow sensor 20 measured in real space can be used as needed.

[0120] Furthermore, the simulation unit 140 may calculate the pressure distribution and the temperature distribution in the measuring line by using the fluid simulation unit 141. Then, for example, particularly when the measuring fluid is a gas, the calculation unit 150 may correct the virtual flow rate Q with respect to the calculated pressure and temperature distribution in the measuring line.

[0121] In this manner, the virtual flow rate calculation device 100 according to the present embodiment can function as at least one of a virtual Coriolis flowmeter, a virtual ultrasonic flowmeter, a virtual electromagnetic flowmeter, or a virtual vortex flowmeter, for example.

[0122] Conventional technologies do not account for external environmental factors in the user's environment, such as the flow of the flow meter unit and pipe vibration, and do not simulate the flow meter output in real time. Furthermore, flow measurement is affected by the influence of the flow velocity distribution within the measurement pipe, which varies depending on the operating environment, and the fluid's physical properties themselves vary due to multiphase conditions, which can affect measurement accuracy. However, considering these factors, it is extremely difficult to estimate the actual flow rate output by the flow meter.

[0123] On the other hand, the virtual flow rate calculation device 100 according to this embodiment assumes usage conditions such as the operating environment of the flow sensor 20 and the physical properties of the fluid being measured in real space, performs simulations related to fluid measurement in virtual space, and calculates a virtual flow rate based on the simulation results. Therefore, the virtual flow rate calculation device 100 according to this embodiment can accurately estimate the actual flow rate measured by the flow sensor 20 based on the user's actual usage environment and usage conditions such as the physical properties of the fluid. Therefore, the virtual flow rate calculation device 100 according to this embodiment can support the operation of flow rate measurements by the flow sensor 20 measured in real space and affected by usage conditions, ultimately achieving stable operation of the instrument system.

[0124] Furthermore, the virtual flow rate calculation device 100 according to this embodiment can diagnose the flow sensor 20 based on the actual flow rate and the virtual flow rate. In this case, if the difference between the actual flow rate and the virtual flow rate does not meet a reference, the virtual flow rate calculation device 100 according to this embodiment can issue an alarm. Therefore, according to the virtual flow rate calculation device 100 according to this embodiment, it is possible to diagnose whether the flow sensor 20 itself is functioning properly or whether the flow sensor 20 is measuring correctly based on whether the calculated virtual flow rate is the expected value compared to the actual flow rate. Furthermore, if an abnormality is suspected (perhaps an unexpected situation has occurred in the flow sensor 20), the user can be notified of this fact.

[0125] Furthermore, the virtual flow rate calculation device 100 according to this embodiment can determine the processing in the calculation unit 150 based on the actual flow rate and the virtual flow rate during a period in which the operation of the flow sensor 20 is considered normal. Therefore, according to the virtual flow rate calculation device 100 of this embodiment, the algorithm of the calculation process can be learned so that the calculated virtual flow rate is close to the actual flow rate during a normal period.

[0126] Furthermore, the virtual flow rate calculation device 100 according to this embodiment functions as at least one of a virtual Coriolis flowmeter, a virtual ultrasonic flowmeter, a virtual electromagnetic flowmeter, or a virtual vortex flowmeter based on the results of at least one of stress simulation, fluid simulation, electromagnetic field simulation, or ultrasonic simulation performed in a virtual space, preferably including coupled simulations comprising a combination thereof. Therefore, the virtual flow rate calculation device 100 according to this embodiment calculates a virtual flow rate based on the various simulation results, and thus can accurately calculate a virtual flow rate based on the sensing principle of the flowmeter.

[0127] Here, in order to estimate the flowmeter output taking into account the effects of the usage environment and multiphase state, a high-speed computing unit and a large-capacity memory are required, but it is extremely difficult to set up these inside the flowmeter. On the other hand, the virtual flow calculation device 100 according to this embodiment can be provided by a cloud server. Therefore, according to the virtual flow calculation device 100 of this embodiment, the processing power, memory capacity, and power consumption limitations of the processor installed in the flowmeter in real space can be eliminated. Therefore, according to the virtual flow calculation device 100 of this embodiment, by increasing the amount of data and the degree of freedom of calculation, it is possible to obtain flow output that combines various metering conditions of the flowmeter.

[0128] Figure 7 An example block diagram of a virtual flow rate calculation device 100 and a sensor module 10 according to a first variation is shown. In the above embodiment, the virtual flow rate calculation device 100 performs a simulation each time it calculates a virtual flow rate. However, in this variation, the virtual flow rate calculation device 100 reuses at least a portion of the simulation results.

[0129] The virtual flow rate calculation device 100 according to the present modification further includes a simulation result storage unit 710. In the present modification, the simulation unit 140 adds the simulation result to the calculation unit 150 and supplies the simulation result to the simulation result storage unit 710.

[0130] The simulation result storage unit 710 stores simulation results. For example, the simulation result storage unit 710 may be a database and may store the results simulated by the simulation unit 140 so that they can be accessed from the calculation unit 150.

[0131] The calculation unit 150 may access the simulation result storage unit 710 to obtain the stored results. The calculation unit 150 may then reuse at least a portion of the stored results when calculating the virtual traffic.

[0132] The virtual flow rate calculation device 100 according to this variation can store simulation results from past runs and reuse at least a portion of the simulation results. Therefore, since the calculated results have already been stored, the virtual flow rate calculation device 100 according to this variation does not need to re-simulate under previously executed conditions. This reduces the computational load and allows for analysis that considers multiple conditions through the learning computation module (AI analysis). Furthermore, the virtual flow rate calculation device 100 according to this variation does not always need to perform a full model simulation, including stress, fluid, electromagnetic field, and ultrasonic propagation simulations, in real time. By pre-storing simulation results under various conditions and recursively obtaining simulation results from the stored results, the amount of computation required to be performed in real time can be significantly reduced.

[0133] Figure 8 An example of a block diagram of a virtual flow rate calculation device 100 and a sensor module 10 according to a second variation is shown. In the above embodiment, the virtual flow rate calculation device 100 diagnoses the flow rate sensor 20 based on the virtual flow rate. However, in this variation, the virtual flow rate calculation device 100 identifies the fluctuation trend of the virtual flow rate.

[0134] The virtual flow rate calculation device 100 according to this modification further includes a tendency identification unit 810 , a notification unit 820 , and a recommendation unit 830 .

[0135] For example, the calculation unit 150 can calculate different virtual flow rates when at least one variable in the environmental information or physical property information varies. For example, the calculation unit 150 can calculate different virtual flow rates when the fluid temperature varies within a range of ±10°C. The calculation unit 150 can supply these virtual flow rates calculated under different conditions, along with the conditions used to calculate the virtual flow rates, to the trend identification unit 810.

[0136] Based on the information supplied from the computing unit 150, the trend identification unit 810 can obtain a trend between a variable that has changed (e.g., fluid temperature) and the virtual flow rate. For example, in this manner, the trend identification unit 810 can identify a trend in the virtual flow rate when at least one variable among the environmental information or the physical property information changes.

[0137] Here, in the environmental information or physical property information, there are variables that are insensitive to virtual flow rates and variables that have certain trends (e.g., monotonically increasing, monotonically decreasing, or trends due to functions). When a variable with a certain trend is discovered, the trend identification unit 810 can provide information about the trend to the notification unit 820. In this case, for example, the trend identification unit 810 can derive multiple curves obtained by approximating the data of the scatter plot of the variable and the virtual flow rate using various types of approximations (e.g., linear approximation, exponential approximation, logarithmic approximation, polynomial approximation, power approximation, etc.), and select the curve with the largest squared correlation coefficient between the scatter plot data and each curve (the closer to 1, the stronger the correlation, the closer to 0, the weaker the correlation) as the approximation curve. In addition, the trend identification unit 810 can form a mathematical expression for the selected approximation curve and calculate a correction function from the mathematical expression. For example, the trend identification unit 810 can provide information indicating such an approximation curve or correction function to the notification unit 820 as information about the trend.

[0138] Then, the notification unit 820 can notify the sensor module 10 of the information about the tendency via the device-side communication unit 130. For example, in this way, the notification unit 820 can notify the sensor module 10 including the flow sensor 20 of the information about the tendency.

[0139] Therefore, in this variation, the sensor module 10 may further include a tendency characteristic storage unit 50. The tendency characteristic storage unit 50 may store information regarding the tendency notified from the virtual flow rate calculation device 100 as a tendency characteristic. The processing unit 30 may then perform signal processing on the output signal from the sensor based on the tendency characteristic stored in the tendency characteristic storage unit 50. As an example, the processing unit 30 may perform correction processing on the output signal from the sensor by using a correction function stored in the tendency characteristic storage unit 50.

[0140] When there are multiple flow sensors 20 for which virtual flow rates are to be calculated, the trend identification unit 810 may further identify, for each flow sensor 20, the trend of the virtual flow rate when at least one variable varies. Note that the multiple flow sensors 20 may differ from one another in at least one of vendor and sensing principle. In this case, the trend identification unit 810 may supply information regarding the identified trend for each flow sensor 20 to the recommendation unit 830.

[0141] The recommendation unit 830 can then determine a recommended flow sensor 20 from among the multiple flow sensors 20 based on the tendency of each flow sensor 20. For example, the recommendation unit 830 can compare the fluctuation range of the virtual flow rate with respect to one or more selected variables (e.g., temperature, viscosity, Reynolds number, etc.) among the multiple flow sensors 20 and determine the flow sensor 20 with the smallest fluctuation as the recommended flow sensor 20. In this way, for example, the virtual flow rate calculation device 100 according to this variation can compare the fluctuation characteristics of multiple flow sensors 20 of various types from various suppliers and recommend to the user the flow sensor 20 that best suits the usage environment.

[0142] In the above description, it is assumed that the fluid to be measured is a single-phase flow. However, in reality, multiple substances (including unexpected substances) may mix to form a multiphase flow.

[0143] Here, "multiphase flow" refers to a fluid that is a mixture of multiple substances with different physical properties. Examples of multiphase flow include gas-liquid two-phase flow, solid-gas two-phase flow, solid-liquid two-phase flow, and solid-gas-liquid three-phase flow, based on the combination of phases (gas, liquid, solid). Furthermore, "multiphase flow" is not necessarily limited to fluids having multiple phases and can also be interpreted as including fluids having a single phase, such as a fluid that is a mixture of multiple separate substances such as water and oil, that is, a liquid-liquid two-phase flow.

[0144] Figure 9 Shown are examples of multiphase flow patterns. When the fluid is single-phase, the flow state is broadly categorized as laminar or turbulent. On the other hand, when the fluid is multiphase, various flow states exist depending on the physical properties of the mixed substances, flow velocity, pipe geometry, and other factors. Flow patterns are classified by capturing the characteristics of these flow states.

[0145] The upper left corner of this figure shows a dispersed flow based on a liquid phase. For example, gases (bubbles, etc.) or solids (sand, slurry, etc.) can flow in a dispersed manner within a fluid that mainly contains a liquid. In addition, other liquids (droplets, etc.) with different physical properties can flow in a dispersed manner without being completely mixed with the main liquid (for example, trace amounts of oil are dispersed in water and flow, or trace amounts of water are dispersed in oil and flow). As described above, when particles of gas, solid, liquid, etc. are dispersed in a liquid phase and flow, a dispersed flow based on a liquid phase may be generated.

[0146] The upper right corner of this figure illustrates dispersed gas-phase flow. For example, a solid or liquid can flow in a dispersed manner within a fluid primarily composed of gas. As described above, dispersed gas-phase flow can occur when particles of a solid, liquid, or the like are dispersed and flow within a gas phase.

[0147] The lower left corner of this figure illustrates laminar flow in a gas-liquid two-phase flow. For example, when a pipeline extends in a generally horizontal direction, the liquid can flow through the lower layer (bottom layer) within the pipeline, while the gas can flow through the upper layer. As described above, laminar flow can occur when multiple components (multiple phases) with different properties flow in a laminar manner.

[0148] The lower right corner of this figure illustrates annular flow in a gas-liquid two-phase flow. For example, when a pipeline extends in a generally vertical direction, the liquid can flow concentrically through the outer layer (on the wall) of the pipeline, while the gas can flow through the inner layer (center) of the pipeline. As described above, annular flow can occur when multiple components (multiple phases) with different properties flow in an annular pattern.

[0149] In multiphase flow, there are various combinations of phases and flow patterns described above. When the fluid under test is in a multiphase flow, a discrepancy may occur between the actual flow rate measured by the flow sensor 20 and the virtual flow rate due to degradation or fluctuations in the sensing signal. This discrepancy is affected by various factors related to the multiphase flow state. In this regard, in the second embodiment, the virtual flow rate calculation device 100 also considers the multiphase state of the fluid under test when calculating the virtual flow rate.

[0150] In the second embodiment, description of the common points with the above-described embodiment will be omitted, and only the differences will be described, but the virtual flow rate calculation device 100 according to the second embodiment can also provide functions similar to those of the virtual flow rate calculation device 100 according to the above-described embodiment. In addition, the virtual flow rate calculation device 100 according to the second embodiment can also be modified similarly to the virtual flow rate calculation device 100 according to the above-described embodiment (for example, as in the first modification and the second modification).

[0151] In the virtual flow rate calculation device 100 according to the second embodiment, the simulation unit 140 may further include a multiphase fluid simulation unit 145 that performs multiphase fluid simulation. The multiphase fluid simulation unit 145 can simulate the flow phenomenon of multiphase flow in a fluid in a virtual space that reproduces the real space by using environmental information and physical property information. The calculation unit 150 can then calculate the virtual flow rate based on the results of this simulation.

[0152] That is, a virtual flow rate calculation device 100 may be provided, comprising: an environment information storage unit 110 that stores environment information indicating the environment of a real space measured by a flow sensor 20; a physical property information storage unit 120 that stores physical property information indicating the physical properties of a fluid to be measured; a simulation unit 140 that simulates a flow phenomenon of a multiphase flow in a fluid in a virtual space that reproduces the real space by using the environment information and the physical property information; and a calculation unit 150 that calculates a virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor 20 based on the simulation result. Similar to the virtual flow rate calculation device 100 according to the above-described embodiment, this virtual flow rate calculation device 100 is preferably provided by a cloud server.

[0153] In addition, a virtual flow calculation method executed by a computer can be provided, comprising: storing environmental information indicating the environment of the real space measured by the flow sensor 20; storing physical property information indicating the physical properties of the fluid to be measured; performing a simulation of the flow phenomenon of multiphase flow in the fluid in a virtual space that reproduces the real space by using the environmental information and the physical property information; and calculating a virtual flow as an estimate of the actual flow measured by the flow sensor 20 based on the result of the simulation.

[0154] In addition, a virtual flow calculation program can be provided, which, when executed by a computer, causes the computer to function as: an environmental information storage unit 110, which stores environmental information indicating the environment of the real space measured by the flow sensor 20; a physical property information storage unit 120, which stores physical property information indicating the physical properties of the fluid to be measured; a simulation unit 140, which simulates the flow phenomenon of multiphase flow in the fluid in a virtual space that reproduces the real space by using the environmental information and the physical property information; and a calculation unit 150, which calculates a virtual flow as an estimate of the actual flow measured by the flow sensor 20 based on the result of the simulation.

[0155] Here, when performing a multiphase fluid simulation, the simulation unit 140 may use an analysis model selected based on at least one of the combination of phases in the multiphase flow or the flow pattern. This analysis model may be a physical model of the multiphase flow, such as a continuous phase model or a dispersed phase model. Note that the analysis model may be manually selected, but the simulation unit 140 may automatically select the model based on a predetermined rule.

[0156] As an example, when macroscopically capturing multiphase flow and roughly analyzing the flow, the simulation unit 140 may use a continuous phase model, such as the Euler-Euler method, in which all phases are treated as continuous phases in an Euler manner.

[0157] On the other hand, when microscopically capturing multiphase flow and tracking particles individually, the simulation unit 140 may use a dispersed phase model, such as the Euler-Lagrangian method, in which particles dispersed in a continuous phase are individually treated in a Lagrangian manner.

[0158] The specific calculation of the virtual flow rate when such a multiphase fluid simulation is also performed will be explained in detail with respect to the sensing principle of each flow meter.

[0159] Figure 10 FIG. 1 shows an example of a block diagram of a virtual flow calculation device 100 according to the second embodiment used as a virtual Coriolis flowmeter. Figure 3 Components having the same functions and configurations are denoted by the same reference numerals, and descriptions other than the differences will be omitted. In the virtual flow rate calculation device 100 according to the second embodiment, in addition to the fluid simulation unit 141, the stress simulation unit 142, and the electromagnetic field simulation unit 143, the simulation unit 140 may further include a multiphase fluid simulation unit 145. In the second embodiment, the virtual flow rate calculation device 100 may use the multiphase fluid simulation unit 145 to perform a multiphase fluid simulation when estimating the output value of a Coriolis flowmeter to be used in real space.

[0160] As described above, in a virtual Coriolis flowmeter, the virtual flow rate Q can be calculated based on the phase time difference τ. However, for example, when the fluid to be measured is a gas-liquid two-phase flow, the Coriolis force acting on the flow tube changes with the flow rate of each phase and the position within the flow tube, and the phase time difference τ also changes accordingly. In this regard, the simulation unit 140 can calculate the flow rate of each phase and the distribution position of the bubbles within the flow tube by performing a multiphase fluid simulation using the multiphase fluid simulation unit 145. Then, the calculation unit 150 can calculate the phase difference generated in the vibration detection sensor from the results of the coupled simulation of the multiphase fluid, stress, and electromagnetic field. And the phase difference The phase time difference τ is calculated by dividing it by the excitation frequency fr of the oscillator.

[0161] At this time, the virtual flow calculation device 100 can estimate the actual flow rate of the Coriolis flowmeter based on the simulation results, and can also estimate other various parameters by performing theoretical calculations using the simulation results.

[0162] For example, the virtual flow rate calculation device 100 can estimate the density of the fluid to be measured from the resonant frequency of the flow tube. For example, the simulation unit 140 can perform a coupled simulation of multiphase fluid and stress. The calculation unit 150 can calculate the resonant frequency fv of the entire flow tube containing the fluid from the simulation results. The calculation unit 150 can then estimate the fluid density p using the following equation. Specifically, the calculation unit 150 can estimate the fluid density p by multiplying the square of the value obtained by dividing the resonant frequency fl of the flow tube in a vacuum by the resonant frequency fv of the entire flow tube containing the fluid, and then multiplying it by the coefficient C.

[0163] (Mathematical formula 7)

[0164]

[0165] Calculation unit 150 can also estimate the fraction of multiphase flow based on the resonant frequency of the flow tube. For example, assume that the resonant frequency fref0 of the flow tube when the fluid is solely in the gas phase and the resonant frequency fref1 of the flow tube when the fluid is solely in the liquid phase are pre-stored. In this case, calculation unit 150 can estimate the gas fraction in the liquid by comparing the calculated resonant frequency fv of the flow tube with the known resonant frequencies fref0 and fref1 of the flow tube. As described above, when flow sensor 20 is a Coriolis flowmeter, calculation unit 150 can estimate at least one of the density of the fluid or the fraction of multiphase flow based on the resonant frequency of the flow tube.

[0166] Furthermore, in a Coriolis flowmeter, the flow tube vibrates under the excitation force of an oscillator. For example, when bubbles are contained in the liquid, the damping of the flow tube increases, and therefore the drive current applied to the oscillator increases to compensate for the excitation. In this regard, the virtual flow calculation device 100 can also estimate the multiphase flow fraction based on this drive current. For example, the simulation unit 140 can perform a coupled simulation of multiphase fluid, stress, and electromagnetic fields. The calculation unit 150 can calculate the drive current applied to the oscillator based on the results of this simulation. It is assumed that a data set indicating the correlation between the drive current applied to the oscillator and the bubble fraction in the liquid is pre-stored. In this case, the calculation unit 150 can estimate the gas fraction in the liquid by comparing the calculated drive current with the known data set. As described above, when the flow sensor 20 is a Coriolis flowmeter, the calculation unit 150 can estimate the multiphase flow fraction based on the drive current applied to the oscillator to vibrate the flow tube.

[0167] For example, the calculation unit 150 can notify the diagnostic unit 160 of the parameters estimated in this manner. Then, when the parameters notified from the calculation unit 150 do not meet the predetermined benchmark, the diagnostic unit 160 can issue an alarm. As an example, assume that it is known that a predetermined amount of pollutants are mixed in the fluid in the factory process. In this case, when the parameters notified from the calculation unit 150 (for example, the density of the fluid, the fraction of multiphase flow, etc.) exceed the range assumed from the known amount of pollutants, the diagnostic unit 160 can issue an alarm. For example, in this way, when the parameters estimated by the calculation unit 150 do not meet the predetermined benchmark, the diagnostic unit 160 can issue an alarm. Note that in the second embodiment, the diagnostic unit 160 can also have the functions described in the above embodiment. That is, when the difference between the actual flow rate and the virtual flow rate does not meet the predetermined benchmark, the diagnostic unit 160 can also issue an alarm.

[0168] Figure 11 An example of a block diagram of a virtual flow calculation device 100 according to the second embodiment used as a virtual ultrasonic flow meter is shown. Figure 4 Components having the same functions and configurations are denoted by the same reference numerals, and descriptions other than the differences will be omitted. In the virtual flow rate calculation device 100 according to the second embodiment, in addition to the fluid simulation unit 141 and the ultrasonic propagation simulation unit 144, the simulation unit 140 may further include a multiphase fluid simulation unit 145. In the second embodiment, the virtual flow rate calculation device 100 can then use the multiphase fluid simulation unit 145 to perform a multiphase fluid simulation when estimating the output value of an ultrasonic flow meter to be used in real space.

[0169] As described above, in a virtual ultrasonic flowmeter, the virtual flow rate Q can be calculated from the propagation times t1 and t2 of the ultrasonic wave. However, for example, when the fluid to be measured is a dispersed flow in which particles such as bubbles and bodies are dispersed in the liquid phase, the ultrasonic wave is scattered and reflected due to the particles. As a result, the signal intensity of the ultrasonic wave emitted from the ultrasonic transmitter is reduced when received on the opposite side, or the apparent propagation velocity in the liquid changes. In this regard, the simulation unit 140 can perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to calculate the flow velocity distribution within the pipeline. The calculation unit 150 can then calculate the propagation times t1 and t2 from the results of the coupled simulation of the multiphase fluid and the ultrasonic wave.

[0170] At this point, the virtual flow rate calculation device 100 can estimate the actual flow rate of the ultrasonic flowmeter based on the simulation results, and can also estimate various other parameters by performing theoretical calculations using the simulation results. Furthermore, the virtual flow rate calculation device 100 can diagnose the amount of bubbles and solid particles and estimate their impact on the flow output.

[0171] For example, the size (diameter) of particles such as bubbles and individual particles affects the amplitude and frequency components of scattered reflections. In this regard, the computing unit 150 can analyze the received ultrasonic signal strength for each frequency band and estimate the distribution state (size, etc.) of the particles by combining the analysis results with the simulation results of ultrasonic propagation and multiphase fluid. Therefore, the virtual flow calculation device 100 can diagnose fluid changes, etc. based on the distribution state of the particles. As described above, when the flow sensor 20 is an ultrasonic flowmeter, the computing unit 150 can estimate the distribution state of particles dispersed in the fluid based on the results of analyzing the received ultrasonic signal strength for each frequency band.

[0172] In addition, when particles such as bubbles and individuals flow unevenly, a difference will appear between the received signal strengths of the opposing ultrasonic waves (i.e., the received signal strength of the ultrasonic waves from the upstream side to the downstream side and the received signal strength of the ultrasonic waves from the downstream side to the upstream side). In this regard, the calculation unit 150 can calculate the difference between the received signal strengths of the opposing ultrasonic waves, that is, the degree of imbalance. Here, it is assumed that a data set indicating the correlation between the difference in received signal strength and the uneven distribution state of the particles is pre-stored. In this case, the calculation unit 150 can estimate the uneven distribution state of particles such as bubbles and individuals by comparing the calculated difference in received signal strength with a known data set. As described above, when the flow sensor 20 is an ultrasonic flowmeter, the calculation unit 150 can estimate the uneven distribution state of particles dispersed in the fluid based on the difference between the received signal strengths of the opposing ultrasonic waves.

[0173] For example, the calculation unit 150 may notify the diagnosis unit 160 of the parameters estimated in this manner. Then, when the parameters notified from the calculation unit 150 do not meet a predetermined benchmark, the diagnosis unit 160 may issue an alarm. As an example, the diagnosis unit 160 may monitor the parameters notified from the calculation unit 150 (e.g., the distribution state of particles, the uneven distribution state of particles, etc.) and issue an alarm when the variation value of the parameters exceeds a predetermined range. For example, in this manner, when the parameters estimated by the calculation unit 150 do not meet a predetermined benchmark, the diagnosis unit 160 may issue an alarm.

[0174] Figure 12 An example of a block diagram of a virtual flow rate calculation device 100 according to the second embodiment used as a virtual electromagnetic flow meter is shown. Figure 5 Components having the same functions and configurations are denoted by the same reference numerals, and descriptions other than the differences will be omitted. In the virtual flow rate calculation device 100 according to the second embodiment, in addition to the fluid simulation unit 141 and the electromagnetic field simulation unit 143, the simulation unit 140 may further include a multiphase fluid simulation unit 145. In the second embodiment, the virtual flow rate calculation device 100 can then use the multiphase fluid simulation unit 145 to perform a multiphase fluid simulation when estimating the output value of an electromagnetic flowmeter to be used in real space.

[0175] As described above, in a virtual electromagnetic flowmeter, the virtual flow rate Q can be calculated from the electromotive force e generated by the electrodes. Here, the electromotive force e is calculated by multiplying and integrating the weighting function w, the magnetic flux density B, and the flow velocity v. However, for example, when the fluid to be measured is a dispersed flow in which electrically insulating particles (bubbles, oil, sand, slurry, etc.) are dispersed in a conductive liquid phase (e.g., water), the electrically insulating particles do not contribute to the electromotive force detected by the electrodes. In this regard, the simulation unit 140 can perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to calculate the frequency and area of ​​particles near the electrodes. The calculation unit 150 can then calculate the electromotive force e by incorporating the signal from the portion where the particles are present as zero into the integral calculation. At this point, of course, there are elements omitted in the simulation, so the calculation unit 150 can incorporate a predetermined coefficient that pre-correlates the simulation results with the actual flow rate into the calculation. In this way, the calculation unit 150 can estimate the actual flow rate of the electromagnetic flowmeter by reducing the electromotive force effect of the electrical insulators that will be dispersed in the fluid to be measured.

[0176] At this time, the virtual flow rate calculation device 100 can estimate the actual flow rate of the electromagnetic flowmeter based on the simulation results, and can also estimate other various parameters by performing theoretical calculations using the simulation results.

[0177] For example, when electrically insulating particles rub against the electrode portion, shaking electrical noise is generated. Furthermore, various flow noises are generated in the electrodes of the electromagnetic flowmeter depending on the various conditions of the fluid. This flow noise can be as described in Japanese Patent No. 6229852, so its description is omitted here. In a second embodiment, by including a multiphase fluid simulation unit 145 in the simulation unit 140, the virtual flow calculation device 100 can also establish an association with this flow noise generated in the electrodes of the electromagnetic flowmeter. For example, when the state of the flow of the multiphase flow near the electrode is known, the calculation unit 150 can calculate the amount of change in the multiphase flow fraction in the measuring cross-section of the measuring tube or near the electrode. By pre-correlating such calculation results with the actual flow rate of the electromagnetic flowmeter using a predetermined coefficient, the simulation results in the virtual space can be associated with the flow noise diagnostic signal. Therefore, the calculation unit 150 can identify the electromotive force effect of the electrical insulator in the dispersed phase and the amount of flow noise obtained as a result of the multiphase fluid simulation. As described above, when the flow sensor 20 is an electromagnetic flowmeter, the calculation unit 150 can estimate the amount of flow noise generated in the electrode based on the electromotive force effect of the electrical insulator dispersed in the fluid.

[0178] Furthermore, by comparing the fluctuation value of the electromagnetic flowmeter's process value and the fluctuation value of the flow noise with the result of parametrically calculating the multiphase state, the calculation unit 150 can estimate the multiphase state, thereby knowing the bubble fraction when the dispersed phase is a gas phase, or knowing the oil fraction when the dispersed phase is an oil phase. As described above, when the flow sensor 20 is an electromagnetic flowmeter, the calculation unit 150 can estimate the multiphase flow fraction based on the results obtained by parametrically calculating the simulation results.

[0179] For example, the calculation unit 150 may notify the diagnosis unit 160 of the parameters estimated in this manner. Then, when the parameters notified from the calculation unit 150 do not meet a predetermined benchmark, the diagnosis unit 160 may issue an alarm. As an example, the diagnosis unit 160 may monitor the parameters notified from the calculation unit 150 (e.g., the amount or score of flow noise) and issue an alarm when the variation value of the parameters exceeds a predetermined range. For example, in this manner, when the parameters estimated by the calculation unit 150 do not meet a predetermined benchmark, the diagnosis unit 160 may issue an alarm.

[0180] Figure 13 An example of a block diagram of a virtual flow calculation device 100 according to the second embodiment used as a virtual vortex flowmeter is shown. Figure 6 Components with the same functions and configurations are denoted by the same reference numerals, and descriptions other than the differences will be omitted. In the virtual flow rate calculation device 100 according to the second embodiment, in addition to the fluid simulation unit 141, the simulation unit 140 may further include a stress simulation unit 142, an electromagnetic field simulation unit 143, and a multiphase fluid simulation unit 145. In the second embodiment, the virtual flow rate calculation device 100 can use the multiphase fluid simulation unit 145 to perform multiphase fluid simulation when estimating the output value of a vortex flowmeter to be used in real space.

[0181] As described above, in a virtual vortex flowmeter, the virtual flow rate Q can be calculated using the vortex frequency f and the pipe cross-sectional area A. However, for example, in the case where the fluid to be measured is in a multiphase state of gas and liquid, such as laminar flow and annular flow, when the liquid phase is present on the pipe wall, the apparent pipe inner diameter decreases and the flow velocity increases. In this regard, the simulation unit 140 can perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to calculate the flow velocity distribution within the pipe. The calculation unit 150 can then calculate the virtual flow rate Q of the gas phase alone based on the simulation results.

[0182] At this time, the virtual flow calculation device 100 can estimate the actual flow of the vortex flowmeter based on the simulation results, and can also estimate various other parameters by performing theoretical calculations using the simulation results. In addition, the virtual flow calculation device 100 can also be used to estimate the dryness in the steam process.

[0183] For example, the virtual flow calculation device 100 can estimate the fraction of multiphase flow based on the amplitude of the voltage generated in the piezoelectric element. For example, to detect the vortex frequency f, a method is employed in which the piezoelectric element detects the stress generated by the alternating pressure applied to the vortex generator when generating Karman vortices. However, when a liquid phase is present on the pipe wall, the alternating pressure applied to the vortex generator due to the generation of Karman vortices is reduced compared to when a gas phase exists alone. In this regard, the simulation unit 140 can perform a coupled simulation of the multiphase flow and stress. The calculation unit 150 can calculate the amplitude of the voltage generated in the piezoelectric element from the simulation results and the piezoelectric function, and estimate the liquid fraction in the gas phase based on this amplitude. As described above, when the flow sensor 20 is a vortex flowmeter, the calculation unit 150 can estimate the fraction of multiphase flow based on the amplitude of the voltage generated in the piezoelectric element.

[0184] Furthermore, the virtual flow calculation device 100 can also estimate the fraction of multiphase flow from the noise generated by the piezoelectric element (variations or fluctuations in the flow of the multiphase fluid). For example, when a liquid phase exists on the pipe wall, the piezoelectric element in the vortex generator receives vibrations generated by fluctuations in the liquid phase flow, etc., as noise. Furthermore, even when droplets exist in the gas phase, the droplets collide with the vortex generator, thereby generating noise on the piezoelectric element. In this regard, the simulation unit 140 can perform a coupled simulation of the multiphase fluid, stress, and electromagnetic field. The calculation unit 150 can calculate the noise generated in the piezoelectric element from the results of this simulation and estimate the liquid fraction in the gas phase, etc. from this noise. As described above, when the flow sensor 20 is a vortex flowmeter, the calculation unit 150 can estimate the fraction of multiphase flow based on the noise generated in the piezoelectric element.

[0185] Furthermore, by using the fraction of the multiphase flow (e.g., the fraction of the gas and liquid phases), the simulation unit 140 can perform a multiphase fluid simulation to calculate the flow velocity distribution within the pipeline through the multiphase fluid simulation unit 145. The calculation unit 150 can then calculate a virtual flow rate Q of the gas phase alone from the simulation results. As described above, when the fluid is in a multiphase state of gas and liquid phases, the calculation unit 150 can calculate the virtual flow rate Q of the gas phase alone based on the fraction of the multiphase flow.

[0186] For example, the calculation unit 150 may notify the diagnosis unit 160 of the parameters estimated in this manner. Then, when the parameters notified from the calculation unit 150 do not meet a predetermined benchmark, the diagnosis unit 160 may issue an alarm. As an example, the diagnosis unit 160 may monitor the parameters notified from the calculation unit 150 (e.g., the fraction of multiphase flow, etc.) and issue an alarm when the variation value of the parameters exceeds a predetermined range. For example, in this way, when the parameters estimated by the calculation unit 150 do not meet a predetermined benchmark, the diagnosis unit 160 may issue an alarm.

[0187] As described above, also in the second embodiment, the flow sensor 20 may be at least one of a Coriolis flowmeter, an ultrasonic flowmeter, an electromagnetic flowmeter, or a vortex flowmeter, and the virtual flow calculation device 100 may function as at least one of a virtual Coriolis flowmeter, a virtual ultrasonic flowmeter, a virtual electromagnetic flowmeter, or a virtual vortex flowmeter.

[0188] In flow measurement, the multiphase state within the measurement pipeline can affect measurement accuracy. In this regard, the virtual flow calculation device 100 according to the second embodiment simulates the multiphase flow phenomena within the measured fluid by using environmental information and physical property information, and calculates a virtual flow rate based on the simulation results. Therefore, the virtual flow calculation device 100 according to the second embodiment can further enhance the diversity of flow measurement and flow measurement-related diagnostics.

[0189] Furthermore, the virtual flow rate calculation device 100 according to the second embodiment can estimate not only the actual flow rate based on the sensing principle of the flow meter but also various other parameters, and can issue an alarm when the estimated parameters do not meet predetermined standards. Furthermore, when performing multiphase fluid simulation, the virtual flow rate calculation device 100 according to the second embodiment can use the optimal analysis model based on the multiphase state. For example, when roughly analyzing the flow, a continuous phase model is used to reduce the computational load, while when tracking individual particles, a dispersed phase model is used to obtain detailed simulation results.

[0190] Various embodiments of the present invention may be described with reference to flow charts and block diagrams, in which blocks may represent (1) stages of a process for performing an operation or (2) portions of an apparatus responsible for performing an operation. Specific stages and portions may be implemented by dedicated circuits, programmable circuits equipped with computer-readable instructions stored on a computer-readable medium, and / or processors equipped with computer-readable instructions stored on a computer-readable medium. Dedicated circuits may include digital and / or analog hardware circuits and may include integrated circuits (ICs) and / or discrete circuits. Programmable circuits may include reconfigurable hardware circuits including logical AND, logical OR, logical XOR, logical NAND, logical NOR, and other logical operations, flip-flops, registers, field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), and other memory elements.

[0191] A computer-readable medium may include any tangible device capable of storing instructions for execution by a suitable device. Consequently, a computer-readable medium having instructions stored thereon includes an article of manufacture having instructions that can be executed to create a means for performing the operations specified in the flowchart or block diagram. Examples of computer-readable media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, and the like. More specific examples of computer-readable media may include a floppy disk (registered trademark), a magnetic disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an electrically erasable programmable read-only memory (EEPROM), a static random access memory (SRAM), a compact disc-read-only memory (CD-ROM), a digital versatile disc (DVD), a Blu-ray (registered trademark) disc, a memory stick, an integrated circuit card, and the like.

[0192] Computer-readable instructions may include: assembly instructions, instruction set architecture (ISA) instructions; machine instructions; machine-dependent instructions; microcode; firmware instructions; state-setting data; or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk (registered trademark), JAVA (registered trademark), C++, and traditional procedural programming languages ​​such as the "C" programming language or similar programming languages.

[0193] Computer-readable instructions can be provided locally or via a local area network (LAN), a wide area network (WAN) such as the Internet, etc. to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, or to a programmable circuit to execute the computer-readable instructions, thereby creating a means for performing the operations specified in the flowchart or block diagram. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0194] Figure 14 An example of a computer 9900 in which aspects of the present invention may be embodied in whole or in part is shown. Programs installed in the computer 9900 can cause the computer 9900 to function as or perform operations associated with an apparatus according to an embodiment of the present invention or one or more portions of such an apparatus, and / or cause the computer 9900 to perform a process according to an embodiment of the present invention or a stage of such a process. Such programs can be executed by the CPU 9912 to cause the computer 9900 to perform operations associated with some or all of the blocks in the flowcharts and block diagrams described herein.

[0195] The computer 9900 according to the present embodiment includes a CPU 9912, a RAM 9914, a graphics controller 9916, and a display device 9918, which are interconnected via a main controller 9910. The computer 9900 also includes input / output units such as a communication interface 9922, a hard disk drive 9924, a DVD drive 9926, and an IC card drive, which are connected to the main controller 9910 via an input / output controller 9920. The computer also includes conventional input / output units such as a ROM 9930 and a keyboard 9942, which are connected to the input / output controller 9920 via an input / output chip 9940.

[0196] The CPU 9912 operates according to the programs stored in the ROM 9930 and the RAM 9914, thereby controlling each unit. The graphics controller 9916 acquires image data generated by the CPU 9912 on a frame buffer or the like provided in the RAM 9914 or in itself, and causes the image data to be displayed on the display device 9918.

[0197] The communication interface 9922 communicates with other electronic devices via a network. The hard disk drive 9924 stores programs and data used by the CPU 9912 within the computer 9900. The DVD drive 9926 reads programs or data from the DVD-ROM 9901 and provides the programs or data to the hard disk drive 9924 via the RAM 9914. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0198] The ROM 9930 stores therein a boot program and the like executed at startup of the computer 9900 and / or programs depending on the hardware of the computer 9900. The input / output chip 9940 can also connect various input / output units to the input / output controller 9920 via a parallel port, a serial port, a keyboard port, a mouse port, and the like.

[0199] The program can be provided via a computer-readable medium such as a DVD-ROM 9901 or an IC card. The program is read from the computer-readable medium, installed in the hard disk drive 9924, RAM 9914, or ROM 9930, which are also examples of computer-readable media, and executed by the CPU 9912. The information processing described in these programs is read into the computer 9900, resulting in cooperation between the program and the various types of hardware resources described above. By implementing information operations or processing based on the use of the computer 9900, a device or method can be constructed.

[0200] For example, when communication is performed between the computer 9900 and an external device, the CPU 9912 can execute a communication program loaded on the RAM 9914 to instruct the communication interface 9922 on communication processing based on the processing described in the communication program. Under the control of the CPU 9912, the communication interface 9922 reads transmission data stored in a transmission buffer area provided in a recording medium such as the RAM 9914, the hard disk drive 9924, the DVD-ROM 9901, or an IC card, and transmits the read transmission data to a network or writes reception data received from the network to a reception buffer area provided on the recording medium.

[0201] Furthermore, the CPU 9912 can cause all or a necessary portion of a file or database stored in an external recording medium such as the hard disk drive 9924, the DVD drive 9926 (DVD-ROM 9901), an IC card, or the like to be read into the RAM 9914, and can perform various types of processing on the data on the RAM 9914. The CPU 9912 then writes the processed data back to the external recording medium.

[0202] Various types of information, such as various types of programs, data, tables, and databases, can be stored in the recording medium and information processing can be performed. The CPU 9912 can perform various types of processing on the data read from the RAM 9914, as described in the present disclosure and specified by the instruction sequence of the program, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., and write the results back to the RAM 9914. In addition, the CPU 9912 can search for information in files, databases, etc. in the recording medium. For example, when a plurality of entries (each having an attribute value of a first attribute related to an attribute value of a second attribute) are stored in the recording medium, the CPU 9912 can search for an entry from the plurality of entries for an entry matching the condition specified for the attribute value of the first attribute, and read the attribute value of the second attribute stored in the entry, thereby obtaining the attribute value of the second attribute related to the first attribute that meets the predetermined condition.

[0203] The above-described program or software module can be stored in a computer-readable medium on or near the computer 9900. In addition, a recording medium such as a hard disk or RAM provided within a server system connected to a dedicated communication network or the Internet can be used as a computer-readable medium, thereby supplying the program to the computer 9900 via the network.

[0204] Although the present invention has been described through the embodiments, the technical scope of the present invention is not limited to the above embodiments. It is obvious that those skilled in the art can make various changes or improvements to the above embodiments. It is also obvious from the description of the scope of the claims that embodiments with such changes or improvements can be included in the technical scope of the present invention.

[0205] Note that the operations, processes, steps, and stages of each process performed by the apparatus, system, program, and method shown in the claims, embodiments, or drawings may be performed in any order as long as the order is not indicated by "prior to," "before," or the like, and as long as the output of the previous process is not used for the subsequent process. Even if words such as "first" or "then" are used in the claims, the description, or the drawings to describe the flow of operations, this does not necessarily mean that the processes must be performed in that order.

[0206] Reference Signs List

[0207] 10: sensor module;

[0208] 20: flow sensor;

[0209] 30: processing unit;

[0210] 40: sensor side communication unit;

[0211] 50: tendency characteristic storage unit;

[0212] 100: virtual flow calculation device;

[0213] 110: environmental information storage unit;

[0214] 120: physical property information storage unit;

[0215] 130: device-side communication unit;

[0216] 140: simulation unit;

[0217] 141: Fluid simulation unit;

[0218] 142: stress simulation unit;

[0219] 143: Electromagnetic field simulation unit;

[0220] 144: Ultrasonic propagation simulation unit;

[0221] 145: Multiphase fluid simulation unit;

[0222] 150: computing unit;

[0223] 160: Diagnostic unit;

[0224] 710: simulation result storage unit;

[0225] 810: tendency identification unit;

[0226] 820: notification unit;

[0227] 830: Recommended unit;

[0228] 9900: Computer;

[0229] 9901: DVD-ROM;

[0230] 9910: host controller;

[0231] 9912: CPU;

[0232] 9914: RAM;

[0233] 9916: Graphics controller;

[0234] 9918: Display devices;

[0235] 9920: Input / output controller;

[0236] 9922: Communication interface;

[0237] 9924: Hard disk drive;

[0238] 9926: DVD drive;

[0239] 9930:ROM;

[0240] 9940: Input / output chip; and

[0241] 9942: Keyboard.

Claims

1. A virtual flow calculation device, comprising: an environment information storage unit that stores environment information indicating an environment of a real space measured by the flow sensor; a physical property information storage unit for storing physical property information indicating the physical properties of the fluid to be measured; a simulation unit that simulates a flow phenomenon of a multiphase flow in the fluid in a virtual space that reproduces the real space by using the environmental information and the physical property information; and A calculation unit calculates a virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor based on a result of the simulation. 2 . The virtual flow calculation device according to claim 1 , wherein the flow sensor is at least one of a Coriolis flowmeter, an ultrasonic flowmeter, an electromagnetic flowmeter, or a vortex flowmeter.

3. The virtual flow calculation device according to claim 2, wherein The flow sensor is a Coriolis flow meter, and The calculation unit estimates at least one of a density of the fluid or a fraction of the multiphase flow based on a resonant frequency of a flow tube.

4. The virtual flow calculation device according to claim 2, wherein The flow sensor is a Coriolis flow meter, and The calculation unit estimates the fraction of the multiphase flow based on a drive current to be applied to an oscillator to vibrate the flow tube.

5. The virtual flow calculation device according to claim 2, wherein The flow sensor is an ultrasonic flow meter, and The calculation unit estimates a distribution state of particles dispersed in the fluid based on a result of analyzing a received signal intensity of ultrasonic waves for each frequency band.

6. The virtual flow calculation device according to claim 2, wherein The flow sensor is an ultrasonic flow meter, and The calculation unit estimates a non-uniform distribution state of particles dispersed in the fluid based on a difference between reception signal intensities of opposing ultrasonic waves.

7. The virtual flow calculation device according to claim 2, wherein The flow sensor is an electromagnetic flow meter, and The calculation unit estimates the amount of flow noise generated in the electrode based on an electromotive force effect of an electrical insulator dispersed in the fluid.

8. The virtual flow calculation device according to claim 2, wherein The flow sensor is an electromagnetic flow meter, and The calculation unit estimates the fraction of the multiphase flow based on a result obtained by parametrically calculating a result of the simulation.

9. The virtual flow calculation device according to claim 2, wherein The flow sensor is a vortex flow meter, and The calculation unit estimates the fraction of the multiphase flow based on the amplitude strength of the voltage generated in the piezoelectric element.

10. The virtual flow calculation device according to claim 2, wherein The flow sensor is a vortex flow meter, and The calculation unit estimates the fraction of the multiphase flow based on noise generated in the piezoelectric element.

11. The virtual flow rate calculation device according to claim 9 or 10, wherein When the fluid is in a multiphase state of gas and liquid, The calculation unit calculates a virtual flow rate of the gas phase alone based on the fraction of the multiphase flow.

12. The virtual flow rate calculation device according to any one of claims 3 to 10, further comprising a diagnosis unit configured to issue an alarm when the parameter estimated by the calculation unit does not satisfy a predetermined reference. 13 . The virtual flow rate calculation device according to claim 12 , wherein the diagnosis unit further issues an alarm when a difference between the actual flow rate and the virtual flow rate does not satisfy a predetermined reference. 14 . The virtual flow rate calculation device according to claim 1 , wherein the simulation unit uses an analysis model selected according to at least one of a combination of phases or a flow pattern in the multiphase flow. 15 . The virtual flow calculation device according to claim 14 , wherein the analytical model is a continuous phase model or a dispersed phase model.

16. The virtual flow calculation device according to any one of claims 1 to 10, wherein the virtual flow calculation device is provided by a cloud server.

17. A method for calculating virtual flow rate executed by a computer, comprising: storing environmental information indicating the environment of a real space being metered by the flow sensor; storing physical property information indicating the physical properties of the fluid to be measured; performing a simulation of a flow phenomenon of a multiphase flow in the fluid in a virtual space that reproduces the real space by using the environmental information and the physical property information; and A virtual flow rate that is an estimate of an actual flow rate measured by the flow sensor is calculated based on the result of the simulation.

18. A virtual flow rate calculation program which, when executed by a computer, causes the computer to function as: an environment information storage unit that stores environment information indicating an environment of a real space measured by the flow sensor; a physical property information storage unit for storing physical property information indicating the physical properties of the fluid to be measured; a simulation unit that simulates a flow phenomenon of a multiphase flow in the fluid in a virtual space that reproduces the real space by using the environmental information and the physical property information; and A calculation unit calculates a virtual flow rate that is an estimate of the actual flow rate measured by the flow sensor based on a result of the simulation.

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