Virtual flow rate calculation device, virtual flow rate calculation method, and virtual flow rate calculation program

Abstract

To provide a virtual flow rate calculation device, a virtual flow rate calculation method, and a virtual flow rate calculation program that estimate the amount of flow noise generated at an electrode based on a density of a fluid and / or a fraction of a multiphase flow, a distribution state and an uneven distribution state of particles dispersed in the fluid, electromotive force effect of an electrical insulator, and electromotive force effect of an electrical insulator.SOLUTION: A virtual flow rate calculation device 100 functioning as a virtual Coriolis flowmeter includes an environmental information storage unit that stores environmental information indicating an environment of the real space in which a flow rate sensor is instrumented, a physical property information storage unit that stores physical property information indicating physical properties of a fluid to be measured, a simulation unit that uses the environmental information and the physical property information to simulate a flow phenomenon of a multiphase flow in the fluid in a virtual space that reproduces the real space, and a calculation unit that calculates a virtual flow rate obtained by estimating an actual flow rate measured by the flow rate sensor based on the simulation results.SELECTED DRAWING: Figure 10

Description

[Technical Field]

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

[0002] Patent Document 1 states, "We provide a flowmeter design support system that can improve the measurement accuracy of differential pressure flowmeters and reduce the risk of non-negligible errors in flow rate indication values ​​occurring in actual equipment at the design stage." [Prior art document] [Patent Documents] [Patent Document 1] JP 2020-144662 [Patent Document 2] JP 2019-194424 [Patent Document 3] JP 2012-132797 [Patent Document 4] JP 2009-014726 A Summary of the Invention

[0003] A first aspect of the present invention provides a virtual flow rate calculation device comprising: an environmental information storage unit that stores environmental information indicating the environment of a real space in which a flow sensor is installed; 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 uses the environmental information and the physical property information to simulate a multiphase flow phenomenon in the fluid in a virtual space that reproduces the real space; and a calculation unit that calculates a virtual flow rate that estimates an actual flow rate actually measured by the flow sensor based on the results of the simulation.

[0004] In the virtual flow rate calculation device, the flow rate sensor may be at least one of a Coriolis flowmeter, an ultrasonic flowmeter, an electromagnetic flowmeter, and a vortex flowmeter.

[0005] In any of the virtual flow rate calculation devices, the flow rate sensor may be the Coriolis flowmeter, 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.

[0006] In any of the virtual flow rate calculation devices, the flow rate sensor may be the Coriolis flowmeter, and the calculation unit may estimate the fraction of the multiphase flow based on a drive current applied to an oscillator to vibrate a flow tube.

[0007] 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 the distribution state of particles dispersed in the fluid based on the results of analyzing the received ultrasonic signal strength for each frequency band.

[0008] 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 the uneven distribution state of particles dispersed in the fluid based on the difference in received signal strength of opposing ultrasonic waves.

[0009] In any of the virtual flow rate calculation devices, the flow rate sensor may be an electromagnetic flowmeter, and the calculation unit may estimate the amount of flow noise generated at the electrodes based on the electromotive force effect of an electrical insulator dispersed in the fluid.

[0010] 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 fraction of the multiphase flow based on a result of parametrically calculating the simulated result.

[0011] In any of the virtual flow rate calculation devices, the flow rate sensor may be the vortex flowmeter, and the calculation unit may estimate the fraction of the multiphase flow based on the amplitude strength of a voltage generated in a piezoelectric element.

[0012] In any of the virtual flow rate calculation devices, the flow rate 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.

[0013] In any of the virtual flow rate calculation devices, when the fluid is in a gas-liquid two-phase multiphase state, the calculation unit may calculate the virtual flow rate of the gas phase alone based on a fraction of the multiphase flow.

[0014] Any of the virtual flow rate calculation devices may further include a diagnosis unit that issues an alert when a parameter estimated by the calculation unit does not satisfy a predetermined standard.

[0015] In any of the virtual flow rate calculation devices, the diagnosing unit may further issue an alert when the difference between the actual flow rate and the virtual flow rate does not satisfy a predetermined standard.

[0016] In any of the virtual flow rate 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 and a flow pattern.

[0017] In any of the virtual flow rate calculation devices, the analytical model may be a continuous phase model or a dispersed phase model.

[0018] Any of the virtual flow rate calculation devices may be provided by a cloud server.

[0019] A second aspect of the present invention provides a virtual flow rate calculation method, which includes the steps of: storing environmental information indicating the environment of a real space in which a flow sensor is installed; storing physical property information indicating the physical properties of a fluid to be measured; simulating a multiphase flow phenomenon in the fluid in a virtual space that reproduces the real space using the environmental information and the physical property information; and calculating a virtual flow rate that estimates an actual flow rate actually measured by the flow sensor based on the results of the simulation.

[0020] In a third aspect of the present invention, there is provided a virtual flow rate calculation program, which is executed by a computer and causes the computer to function as an environmental information storage unit that stores environmental information indicating the environment of a real space in which a flow sensor is installed, 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 uses the environmental information and the physical property information to simulate a flow phenomenon of a multiphase flow of the fluid in a virtual space that reproduces the real space, and a calculation unit that calculates a virtual flow rate that estimates an actual flow rate actually measured by the flow sensor based on the results of the simulation.

[0021] The above summary of the invention does not list all of the features of the present invention, and subcombinations of these features may also be inventions. [Brief explanation of the drawings]

[0022] [Figure 1] An example of a block diagram of a virtual flow rate calculation device 100 according to this embodiment is shown together with a sensor module 10. [Figure 2] 1 shows an example of a flowchart of a virtual flow rate calculation method executed by a virtual flow rate calculation device 100 according to the present embodiment. [Figure 3] 1 shows an example of a block diagram of a virtual flow rate calculation device 100 that functions as a virtual Coriolis flowmeter. [Figure 4]1 shows an example of a block diagram of a virtual flow rate calculation device 100 that functions as a virtual ultrasonic flow meter. [Figure 5] 1 shows an example of a block diagram of a virtual flow rate calculation device 100 that functions as a virtual electromagnetic flow meter. [Figure 6] 1 shows an example of a block diagram of a virtual flow rate calculation device 100 that functions as a virtual vortex flowmeter. [Figure 7] An example of a block diagram of a virtual flow rate calculation device 100 according to a first modified example is shown together with a sensor module 10. [Figure 8] An example of a block diagram of a virtual flow rate calculation device 100 according to a second modified example is shown together with a sensor module 10. [Figure 9] An example of a multiphase flow pattern is shown below. [Figure 10] 1 shows an example of a block diagram of a virtual flow rate calculation device 100 according to a second embodiment that functions as a virtual Coriolis flowmeter. [Figure 11] FIG. 1 shows an example of a block diagram of a virtual flow rate calculation device 100 according to a second embodiment that functions as a virtual ultrasonic flow meter. [Figure 12] 1 shows an example of a block diagram of a virtual flow rate calculation device 100 according to a second embodiment that functions as a virtual electromagnetic flow meter. [Figure 13] FIG. 1 shows an example of a block diagram of a virtual flow rate calculation device 100 according to a second embodiment that functions as a virtual vortex flowmeter. [Figure 14] 99 illustrates an example computer 9900 in which aspects of the present invention may be embodied, in whole or in part. DETAILED DESCRIPTION OF THE INVENTION

[0023] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention according to the claims. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0024] FIG. 1 shows an example of a block diagram of a virtual flow rate calculation device 100 according to this embodiment, together with a sensor module 10. Note that these blocks are functionally separated functional blocks and do not necessarily correspond to the actual device configuration. In other words, just because something is shown as one block in this diagram does not necessarily mean that it is composed of one device. Also, just because something is shown as separate blocks in this diagram does not necessarily mean that it is composed of separate devices. The same applies to the subsequent block diagrams.

[0025] The sensor modules 10 are installed at various locations in a facility, measure physical quantities of objects to be measured, and transmit the measurement data to other devices. Such facilities may be, for example, a device (or devices) that manufacture products from raw materials. As an example, the facility may be a plant. Examples of plants include industrial plants such as chemical and biotech plants, plants that manage and control wellheads and surrounding areas of gas and oil fields, plants that manage and control power generation such as hydroelectric, thermal, and nuclear power, plants that manage and control environmental power generation such as solar and wind power, and plants that manage and control water supply and sewage systems, dams, etc. The sensor module 10 includes a flow sensor 20, a processing unit 30, and a sensor-side communication unit 40.

[0026] The flow sensor 20 is a measuring instrument that is installed in a real space (for example, a plant pipe or the like) and measures the amount of a fluid to be measured (liquid, gas, steam, powder, or a mixed phase of these) flowing through the pipe per unit time. Examples of such a flow sensor 20 include various flow meters with different sensing principles depending on various conditions such as the purpose of the measurement, the measurement location, the type of fluid, or the state of the fluid. As an example, the flow sensor 20 may be at least one of a Coriolis flow meter, an ultrasonic flow meter, an electromagnetic flow meter, or a vortex flow meter.

[0027] A Coriolis flowmeter is a flowmeter that utilizes the physical phenomenon of the Coriolis force. When a fluid passes through a flow tube that operates at a resonant frequency, inertia causes the flow tube to twist, resulting in a phase shift in the detection signals of the vibration detection sensors attached to the inlet and outlet sides of the flow tube. In a Coriolis flowmeter, for example, this phase shift is detected and multiplied by a coefficient to output the flow rate.

[0028] Ultrasonic flowmeters use the difference in the propagation time of ultrasonic waves. When ultrasonic waves are sent and received diagonally across a fluid in a pipe, the ultrasonic waves travel slower when they are traveling against the flow of the fluid and travel faster when they are traveling with the flow. In ultrasonic flowmeters, the flow velocity is calculated using the difference in the propagation time of two such ultrasonic waves, corrected to the average flow velocity of the surface using a flow correction coefficient, and then multiplied by the cross-sectional area of ​​the pipe to output the flow rate.

[0029] An electromagnetic flowmeter is a flowmeter that uses Faraday's electromagnetic induction. A magnetic field is created by an electromagnet, and when a conductive fluid passes through the magnetic field, an electromotive force proportional to the flow rate is generated in a direction perpendicular to both the direction of the magnetic field and the direction of the fluid flow. In an electromagnetic flowmeter, for example, the magnitude of this electromotive force is detected and multiplied by the cross-sectional area of ​​the pipe to output the flow rate.

[0030] A vortex flowmeter is a flowmeter that uses Karman vortices. When a cylindrical obstacle (vortex generator) is present in a flowing fluid, Karman vortices are generated downstream of it. In this case, the flow velocity of the fluid and the vortex frequency of the Karman vortices are proportional to each other. In a vortex flowmeter, for example, the vortex frequency of these Karman vortices is used to calculate the flow velocity, and the flow rate is output by multiplying this by the cross-sectional area of ​​the pipe.

[0031] The flow sensor 20 may be, for example, at least one of a Coriolis flow meter, an ultrasonic flow meter, an electromagnetic flow meter, or a vortex flow meter. The sensor module 10 may further include another sensor (not shown) capable of measuring a physical quantity different from that of the flow sensor 20. For example, the sensor module 10 may further include another sensor such as a pressure meter, a thermometer, a viscometer, a pH meter, a conductivity meter, or a slurry concentration meter.

[0032] The processing unit 30 processes output signals from the flow sensor 20 and other sensors. The processing unit 30 may supply measurement data obtained by signal processing the output signals from the sensors to the sensor-side communication unit 40. Such measurement data may be data indicating at least the actual flow rate measured by the flow sensor 20.

[0033] 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 in accordance with a communication protocol. The sensor-side communication unit 40 may transmit the measurement data supplied from the processing unit 30 to the virtual flow rate calculation device 100 via a network.

[0034] Generally, the flow sensor 20 is calibrated under standard operating conditions in facilities that are traceable to national standards. For example, the standard operating conditions are: fluid = water, fluid temperature = room temperature ±α, ambient temperature = room temperature ±α, and upstream and downstream straight pipe lengths = sufficiently long. When such a flow sensor 20 is installed in a real space, the operating conditions, such as the type of fluid, fluid temperature, ambient temperature, or upstream and downstream straight pipe lengths, differ from the standard operating conditions at the time of calibration, resulting in a difference from the calibrated value.

[0035] Naturally, suppliers of flow sensors 20 anticipate these types of differences in usage conditions and design their sensors to minimize the effects of usage environment and fluid properties to a certain level. However, when there are changes in the meter due to long-term use or changes in the actual flow equipment, it is necessary to estimate the actual flow rate based on output fluctuations and internal status information of the flow sensor 20 installed in the actual space. Furthermore, to ensure the soundness of the flow sensor 20, it is ultimately necessary to recalibrate it in equipment that is traceable to national standards.

[0036] Therefore, the virtual flow rate calculation device 100 according to this embodiment performs a simulation related to fluid measurement in a virtual space, assuming usage conditions such as the usage environment and fluid properties of the flow sensor 20 installed in the real space, and calculates a virtual flow rate that estimates the above-mentioned actual flow rate based on the simulation results. The virtual flow rate calculation device 100 according to this embodiment includes an environment information storage unit 110, a physical property information storage unit 120, an apparatus-side communication unit 130, a simulation unit 140, a calculation unit 150, and a diagnosis unit 160.

[0037] The environmental information storage unit 110 stores environmental information that indicates the environment of the real space in which the flow sensor 20 is installed. For example, the environmental information storage unit 110 may be a database, and may store environmental information acquired via user input, various memory devices, a network, or the like, so that the information can be accessed by the calculation unit 150.

[0038] 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 acquired via user input, various memory devices, a network, or the like so that the information can be accessed by the calculation unit 150.

[0039] The device-side communication unit 130 includes a communication stack and a communication driver for communicating with the sensor module 10 in accordance with a communication protocol. For example, the device-side communication unit 130 may 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 may supply the acquired measurement data to the diagnosis unit 160.

[0040] The simulation unit 140 uses the environmental information and the physical property information to perform a simulation related to fluid measurement in a virtual space that reproduces a real space. For example, the simulation unit 140 may perform a simulation related to fluid measurement in the virtual space 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 in accordance with an instruction from the calculation unit 150. The simulation unit 140 may supply the simulation results to the calculation unit 150.

[0041] The calculation unit 150 calculates a virtual flow rate that is an estimate of the actual flow rate actually measured by the flow sensor 20 based on the simulation results. For example, the calculation unit 150 may acquire the simulation results from the simulation unit 140 and calculate a virtual flow rate that is an estimate of the actual flow rate actually measured by the flow sensor 20 based on the simulation results. The calculation unit 150 may notify the diagnosis unit 160 of the calculated virtual flow rate.

[0042] The diagnosing unit 160 diagnoses the flow sensor 20 based on the actual flow rate and the virtual flow rate. For example, the diagnosing unit 160 may diagnose the flow sensor 20 by comparing 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.

[0043] The virtual flow rate calculation device 100 equipped with such functional units may be a computer such as a PC (personal computer), tablet computer, smartphone, workstation, server computer, or general-purpose computer, or may be a computer system in which multiple computers are connected. Such a computer system is also a computer in a broad sense. The virtual flow rate calculation device 100 may also be implemented as a virtual computer environment in which one or more programs can be executed within a computer. Alternatively, the virtual flow rate calculation device 100 may be a dedicated computer designed for calculating virtual flow rates, or may be dedicated hardware realized by dedicated circuits. Furthermore, if the virtual flow rate calculation device 100 is connectable to the Internet, it may be realized by cloud computing. In particular, it is preferable that the virtual flow rate calculation device 100 be provided by a cloud server from the standpoints of processing power and memory capacity.

[0044] Furthermore, such a computer may include a memory that stores a virtual flow rate calculation program and a processor that executes the virtual flow rate calculation program, and the processor executes the virtual flow rate calculation program to implement the functions of the virtual flow rate calculation device 100. That is, a virtual flow rate calculation program may be provided that is executed by a computer and causes the computer to function as an environment information storage unit 110 that stores environmental information that indicates the environment of the real space in which the flow sensor 20 is installed, a physical property information storage unit 120 that stores physical property information that indicates the physical properties of the fluid to be measured, a simulation unit 140 that uses the environmental information and the physical property information to perform a simulation related to the measurement of the fluid in a virtual space that reproduces the real space, and a calculation unit 150 that calculates a virtual flow rate that estimates the actual flow rate actually measured by the flow sensor 20 based on the simulation results.

[0045] 2 shows an example of a flow diagram 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 may be performed by a computer. However, as long as the computer is the overall performer of each step, some parts that are not the main parts may be performed by a device other than the computer.

[0046] 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 in which the flow sensor 20 is installed so that the information is accessible from the calculation unit 150. In this case, the environmental information storage unit 110 may store, as environmental information, information on the piping attached to the outside of the flow sensor 20 (straight pipe length, the state of the upstream and downstream elbows, etc.), information on the mounting gasket, information on the fluid (liquid type, concentration, presence or absence of multiphase, expected temperature, expected pressure, etc.), or information on peripheral devices, for example. Note that part of such environmental information, for example, information on the piping, may be extracted from CAD (Computer Aided Design) data, aerial photography data, etc.

[0047] Here, if the usage environment changes over time, the environmental information storage unit 110 may store, as environmental information, measurement data from other sensors such as a pressure gauge, thermometer, viscometer, pH meter, conductivity meter, or slurry concentration meter that are installed in the real space in the same way as the flow sensor 20. Furthermore, the environmental information storage unit 110 may store, as environmental information, measurement data from the flow sensor 20, i.e., the actual flow rate actually measured by the flow sensor 20. In such a case, the environmental information storage unit 110 may store the measurement data in chronological order, assuming that the data will change over time.

[0048] In step S220, the computer stores the physical property information. For example, the physical property information storage unit 120 may store physical property information indicating the physical properties of the fluid to be measured so that the information is accessible from the calculation unit 150. In this case, the physical property information storage unit 120 may store, as the physical property information, information such as density, viscosity, conductivity, electrical resistivity, dielectric constant, or acoustic properties, including the temperature-pressure characteristics of the fluid to be measured. Although the above description illustrates an example in which the physical property information storage unit 120 stores only physical property information indicating the physical properties of the fluid to be measured, this is not limiting. The physical property information storage unit 120 may also store physical property information indicating the physical properties of various substances required for the simulation, other than the fluid to be measured. In this case, the physical property information storage unit 120 may store, as the physical property information, various information (e.g., resistivity of metals or temperature characteristics of mechanical properties) listed in so-called scientific chronologies or various basic physical property databases.

[0049] In step S230, the computer acquires measurement data. For example, the device-side communication unit 130 may acquire the measurement data from the sensor module 10 via a network. As described above, such measurement data may be data indicating at least the actual flow rate measured by the flow sensor 20.

[0050] 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 by the flow sensor 20 and measurement data by other sensors) in chronological order.

[0051] In step S240, the computer executes a simulation. For example, the calculation unit 150 may access the environmental information storage unit 110 to acquire environmental information required for the simulation. The calculation unit 150 may also access the physical property information storage unit 120 to acquire physical property information required for the simulation. 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 calculation unit 150 may then provide this information to the simulation unit 140 and instruct it to execute a simulation. In response, the simulation unit 140 may use the environmental information and physical property information to execute a simulation related to fluid measurement in a virtual space that recreates a real space, for example, in a digital twin.

[0052] For example, the simulation unit 140 may perform a 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, and ultrasonic wave in a virtual space.

[0053] For example, in a stress simulation, the simulation unit 140 may simulate the vibration state that is transmitted from a vibration source such as a pump through a pipe and applied to the flow sensor 20. The simulation unit 140 may also simulate the fluid pressure that is applied to the flow sensor 20 based on information from a pressure gauge, a level gauge, etc. The simulation unit 140 may also simulate the stress distribution on the pipe due to bolt fastening between the pipes, stanchions, etc.

[0054] Furthermore, the simulation unit 140 may, for example, input basic information such as the pump head, fluid, and pressure loss throughout the entire piping system to simulate the flow rate of a flow meter used in a real space. In this case, performing a fluid simulation using a full model allows for a direct comparison between the actual flow rate and the virtual flow rate. The advantage of this method is that it is possible to determine the flow velocity distribution across the flow meter cross section, which varies depending on the flow velocity and fluid viscosity. Coriolis flow meters, ultrasonic flow meters, electromagnetic flow meters, and vortex flow meters are susceptible to the influence of flow velocity distribution, but it is possible to estimate whether their output is dependent on the flow velocity distribution. On the other hand, if the performance of the computing device makes it difficult to perform a fluid simulation that takes into account the entire piping of a plant or other facility, the simulation unit 140 may omit some elements and perform the simulation. In this case, discrepancies between the actual flow rate and the virtual flow rate may occur. Therefore, in such cases, the simulation unit 140 may use the setpoint flow rate set by proportional integral differential (PID) control in the control system used in the plant or the actual flow rate during a period considered to be normal operation as the initial value. The simulation unit 140 can reduce the computational load by partially performing fluid simulation, but in this case, it looks at the difference between the virtual flow rate value, which is considered to be in a normal operating state, and the actual flow rate value.

[0055] Furthermore, the simulation unit 140 may, for example, in an electromagnetic field simulation, provide the applied current values ​​of the two coils provided in the flow sensor 20 as initial values, and simulate the magnetic flux density distribution in the cross section of the pipe.

[0056] Furthermore, the simulation unit 140 may simulate, for example, the ultrasonic propagation time and the attenuation of the ultrasonic signal from the fluid properties, plant piping parameters, and environmental temperature in an ultrasonic propagation simulation.

[0057] In this way, the simulation unit 140 may simulate at least one of stress, fluid, electromagnetic field, and ultrasonic wave, and preferably a combination of these, in a virtual space.

[0058] In step S250, the computer calculates a virtual flow rate. For example, the calculation unit 150 may calculate a virtual flow rate that estimates the actual flow rate measured by the flow sensor 20 based on the results of the simulation performed in step S240. Generally, the flow velocity distribution and fluid properties (fluid pressure, density, viscosity, etc.) change depending on piping conditions, fluid conditions, etc. However, the calculation unit 150 calculates the virtual flow rate based on the results of a simulation using environmental information and physical property information. This allows the calculation unit 150 to reflect the actual usage environment and fluid properties in the calculation and calculate a virtual flow rate that more accurately estimates the actual flow rate. Specific calculations of the virtual flow rate will be described in detail below for each sensing principle of the flow meter.

[0059] The calculation unit 150 may 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 considered to be operating normally. More specifically, if there is a difference between the virtual flow rate calculated during a period when the flow sensor 20 is considered to be operating normally when it is installed in the real space and the actual flow rate, the calculation unit 150 may multiply the calculated virtual flow rate by a ratio corresponding to the difference as a correction value and use the result as the initial result of the virtual flow rate. This allows the virtual flow meter to be calibrated with a correct initial value of flow rate (a flow rate closer to the actual flow rate without any aging error) by adjusting the calculation result of the virtual flow rate to the actual flow rate at an initial stage when no aging error is present, such as immediately after the flow sensor 20 is installed in the real space. The calculation unit 150 may also add calculation conditions for the virtual flow rate (for example, by using measurement data from the real space for the ambient temperature or setting a smaller convergence value for the simulation) to bring the virtual flow rate closer to the actual flow rate through repeated calculations. Furthermore, when calculating the virtual flow rate based on the results of a fluid simulation, the calculation unit 150 may calculate the virtual flow rate based on the results of a fluid simulation using the actual flow rate, and then calculate a virtual flow rate that is even closer to the actual flow rate by repeating the procedure of calculating the virtual flow rate using a fluid simulation using a value that is closer to the actual flow rate.

[0060] In step S260, the computer compares the actual flow rate with the virtual flow rate. For example, the diagnosing 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.

[0061] In step S270, the computer determines whether the difference satisfies a criterion. For example, the diagnosis unit 160 may determine whether the difference between the actual flow rate and the virtual flow rate satisfies a predetermined criterion as a result of the comparison in step S260. If it is determined that the difference satisfies the criterion (Yes) (for example, 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 it is determined that the difference does not satisfy the criterion (No) (for example, the difference is equal to or greater than a threshold), the virtual flow rate calculation device 100 may proceed with the process to step S280.

[0062] In step S280, the computer issues an alert. For example, the diagnosing unit 160 may output a message on a monitor, a sound, a printout, or a signal indicating that the difference does not satisfy the criteria. In this way, for example, the diagnosing unit 160 may issue an alert when the difference between the actual flow rate and the virtual flow rate does not satisfy a predetermined criterion. This allows the diagnosing unit 160 to diagnose the flow sensor 20 based on the actual flow rate and the virtual flow rate.

[0063] Then, the virtual flow rate calculation device 100 ends this flow. Note that the virtual flow rate calculation device 100 can dynamically perform these calculations and diagnoses. For example, the virtual flow rate calculation device 100 may continuously calculate the virtual flow rate and diagnose the flow sensor 20 at a period multiple times the measurement period of the actual flow rate. Also, the virtual flow rate calculation device 100 may calculate the virtual flow rate and diagnose the flow sensor 20 at a timing specified by the user (for example, every hour, every day, or at a timing dependent on an event such as the start of operation). Also, the virtual flow rate calculation device 100 may calculate the virtual flow rate and diagnose the flow sensor 20 at a timing when the fluctuation in the actual flow rate reaches a value specified by the user or the system (for example, 5% of the measurement span), when the conditions input into the environmental information or physical property information are changed, or when the change exceeds a value specified by the user or the system (for example, 5%).

[0064] As explained using this flow, a virtual flow rate calculation method may be provided, which includes the steps of: a computer storing environmental information indicating the environment of the real space in which the flow sensor 20 is installed; storing physical property information indicating the physical properties of the fluid to be measured; using the environmental information and the physical property information to perform a simulation related to the measurement of the fluid in a virtual space that reproduces the real space; and calculating a virtual flow rate that estimates the actual flow rate actually measured by the flow sensor 20 based on the simulation results. Specific calculations of the virtual flow rate will now be described in detail for each type of flow meter.

[0065] 3 shows an example of a block diagram of the virtual flow rate calculation device 100 functioning as a virtual Coriolis flowmeter. The virtual flow rate calculation device 100 may function as a virtual Coriolis flowmeter. When functioning 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 may estimate the output value of a Coriolis flowmeter used in real space using, for example, the fluid simulation unit 141, the stress simulation unit 142, and the electromagnetic field simulation unit 143.

[0066] More specifically, if a coefficient SK is a function of structural features such as the shape of the flow tube and the position of the vibration detection sensor, and a phase time difference τ is calculated from the phase difference between vibrations occurring upstream and downstream of the flow tube, the calculation unit 150 may calculate the virtual flow rate Q using the following equation: That is, the calculation unit 150 may calculate the virtual flow rate Q as the product of the coefficient SK and the phase time difference τ. Here, the phase time difference τ is the phase difference φ occurring in the vibration detection sensor divided by the excitation frequency fr of the oscillator. Therefore, the virtual flow rate Q can also be expressed as the product of the coefficient SK and the phase difference φ divided by the excitation frequency fr.

number

[0067] In this case, in relation to the coefficient SK, the simulation unit 140 may perform a stress simulation using the stress simulation unit 142. As an example, the stress simulation unit 142 may input a 3D model of the flow tube, oscillator, and vibration detection sensor under normal temperature and pressure, as well as temperature and pressure obtained from a meter in real space, and output the flow tube shape of a virtual Coriolis flowmeter. Furthermore, the stress simulation unit 142 may input the flow tube shape and the Young's modulus under the same conditions, and output the resonant frequency and moment of inertia of the flow tube required to calculate the coefficient SK.

[0068] The calculation unit 150 may then calculate characteristic quantities such as the natural angular frequency from the results of a stress simulation that takes into account the temperature and pressure acting on the flow tube and the excitation force of the oscillator that powers the vibration of the flow tube, and calculate the coefficient SK by substituting the calculated characteristic quantities into a function that uses the previously derived characteristic quantities as variables.

[0069] Furthermore, in relation to the phase time difference τ, the simulation unit 140 may perform a coupled simulation 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 time difference τ by calculating the phase difference φ occurring in the vibration detection sensor from the results of the coupled simulation and dividing this by the excitation frequency fr of the oscillator.

[0070] 4 shows an example of a block diagram of the virtual flow rate calculation device 100 functioning as a virtual ultrasonic flow meter. The virtual flow rate calculation device 100 may function as a virtual ultrasonic flow meter. When functioning as a virtual ultrasonic flow meter, the simulation unit 140 may include, for example, a fluid simulation unit 141 and an ultrasonic propagation simulation unit 144. The virtual flow rate calculation device 100 may estimate the output value of an ultrasonic flow meter used in real space using, for example, the fluid simulation unit 141 and the ultrasonic propagation simulation unit 144.

[0071] More specifically, if the angle between the measurement pipe axis and the ultrasonic propagation axis is θ, the distance the ultrasonic waves propagate is L, the propagation time of the ultrasonic waves from the upstream side to the downstream side is t1, and the propagation time of the ultrasonic waves from the downstream side to the upstream side is t2, the calculation unit 150 may calculate the flow velocity v using the following formula: That is, the calculation unit 150 may calculate the flow velocity v using a function of the reciprocal difference (frequency difference) of the propagation times.

number

[0072] Then, assuming that the flow rate correction coefficient is k and the cross-sectional area of ​​the pipeline is A, the calculation unit 150 may calculate the virtual flow rate Q using the following formula: That is, the calculation unit 150 may calculate the virtual flow rate by correcting the flow velocity v to the average flow velocity of the cross section through which the fluid flows using the flow rate correction coefficient k, and then multiplying this by the cross-sectional area A of the pipeline.

number

[0073] At this time, in relation to the propagation times t1 and t2, the simulation unit 140 may perform a fluid simulation using the fluid simulation unit 141. As an example, the fluid simulation unit 141 may calculate a three-dimensional flow velocity distribution in the measurement pipe taking into account the upstream and downstream straight pipe lengths, upstream and downstream elbows, fluid viscosity, etc. At this time, the actual flow rate (flow velocity) output value of the flow sensor 20 installed in the real space may be used as necessary.

[0074] Furthermore, the simulation unit 140 may perform an ultrasonic propagation simulation using the ultrasonic propagation simulation unit 144. As an example, the ultrasonic propagation simulation unit 144 may calculate the propagation time of ultrasonic waves emitted from the piezoelectric elements in the upstream-to-downstream direction and the downstream-to-upstream direction at the installation positions of the upstream and downstream sensors when the flow rate is zero. The ultrasonic propagation simulation unit 144 may then simulate the propagation of ultrasonic waves by calculating the propagation time in consideration of piping parameters such as pipe wall thickness and scale, and temperatures (environmental temperature, fluid temperature).

[0075] The calculation unit 150 may 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 a coupled analysis using the propagation time based on the simulation results of the three-dimensional flow velocity distribution in the measurement pipe and ultrasonic propagation. The coupled analysis can calculate the propagation times t1 and t2 by combining the propagation time calculated by the ultrasonic propagation simulation with the three-dimensional flow velocity distribution calculated by the fluid simulation.

[0076] 5 shows an example of a block diagram of the virtual flow rate calculation device 100 functioning as a virtual electromagnetic flow meter. The virtual flow rate calculation device 100 may function as a virtual electromagnetic flow meter. When functioning as a virtual electromagnetic flow meter, 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 may estimate the output value of an electromagnetic flow meter used in real space using, for example, the fluid simulation unit 141 and the electromagnetic field simulation unit 143.

[0077] More specifically, the calculation unit 150 may calculate the electromotive force e generated in the electrode using the following equation: That is, the calculation unit 150 may calculate the electromotive force e by multiplying and integrating the weighting function w, the magnetic flux density B, and the flow velocity v.

number

[0078] Then, the calculation unit 150 may calculate the virtual flow rate Q using the following equation: That is, the calculation unit 150 may calculate the virtual flow rate Q using the calculated electromotive force e, the pipe inner diameter D, and the constant K.

number

[0079] Here, in relation to the magnetic flux density B, the simulation unit 140 may use the electromagnetic field simulation unit 143 to perform an electromagnetic field simulation. As an example, the electromagnetic field simulation unit 143 may input the dimensions of the coil and magnetic material of the electromagnetic flowmeter and the physical properties of the magnetic material to calculate the magnetic flux density distribution inside the measurement pipe. In this case, for the magnetic flux density, the magnetic flux density distribution inside the measurement pipe that has actually been measured may be stored as a database. This method can be used when there is no design information for at least one of the coil, dimensions of the magnetic material, or physical properties of the magnetic material of a competitor's product.

[0080] Furthermore, in relation to the flow velocity v, the simulation unit 140 may perform a fluid simulation using the fluid simulation unit 141. As an example, the fluid simulation unit 141 may calculate the flow velocity distribution at the cross section of the measurement pipeline, taking into account the upstream and downstream straight pipe lengths, upstream and downstream elbows, fluid viscosity, etc. At this time, the actual flow rate (flow velocity) output value of the flow sensor 20 installed in the real space may be used as necessary.

[0081] The weighting function w is a function of the electric field (magnetic flux density × flow velocity) generated at each point in the measurement pipe and the distance between the electrodes, and for example, a weighting function described in JIS B 7554 or a weighting function based on the electrode shape and arrangement position may be used.

[0082] The calculation unit 150 may then calculate the electromotive force e generated at the electrode by multiplying the electric field (magnetic flux density B × flow velocity v) generated at each point in the measurement pipe by a weighting function w and integrating the result. In this case, since the material properties may have a certain range, the calculated electromotive force e may be multiplied by a certain coefficient.

[0083] 6 shows an example of a block diagram of the virtual flow rate calculation device 100 functioning as a virtual vortex flowmeter. The virtual flow rate calculation device 100 may function as a virtual vortex flowmeter. When functioning as a virtual vortex flowmeter, the simulation unit 140 may include, for example, a fluid simulation unit 141. The virtual flow rate calculation device 100 may then use, for example, the fluid simulation unit 141 to estimate the output value of the vortex flowmeter used in the real space.

[0084] More specifically, the calculation unit 150 may calculate the virtual flow rate Q using the following equation: That is, the calculation unit 150 may calculate the virtual flow rate Q by multiplying the vortex frequency f by the cross-sectional area A of the pipe and the width d of the vortex shedder, and dividing the result by the Strouhal number St. Note that the Strouhal number St is a dimensionless number determined by the shape and dimensions of the vortex shedder.

number

[0085] Here, in relation to the vortex frequency f, the simulation unit 140 may perform a fluid simulation using the fluid simulation unit 141. As an example, the fluid simulation unit 141 may input the physical properties of the fluid, the shape of the vortex bar, and the piping conditions (straight pipe length, steps, etc.) to simulate the state of vortex generation in the measurement pipeline. In this case, the actual flow rate (flow velocity) output value of the flow sensor 20 installed in the real space may be used as necessary.

[0086] Furthermore, the simulation unit 140 may calculate the pressure distribution and temperature distribution in the measurement pipeline using the fluid simulation unit 141. Then, the calculation unit 150 may correct the virtual flow rate Q for the calculated pressure and temperature distribution in the measurement pipeline, particularly when the measured fluid is a gas, for example.

[0087] In this way, the virtual flow rate calculation device 100 according to this embodiment can function as at least one of a virtual Coriolis flowmeter, a virtual ultrasonic flowmeter, a virtual electromagnetic flowmeter, and a virtual vortex flowmeter.

[0088] Conventional technology does not take into account external environmental factors such as the flow in the flow meter and pipe vibration in the user's environment, and does not simulate flow meter output in real time. Furthermore, in flow measurement, the influence of the flow velocity distribution in the measurement pipe changes depending on the usage environment, and the fluid properties themselves change depending on the multiphase state, which affects measurement accuracy. However, it has been extremely difficult to estimate the actual flow rate of the flow meter output while taking these factors into account.

[0089] In contrast, the virtual flow rate calculation device 100 according to this embodiment performs a simulation related to fluid measurement in a virtual space, assuming usage conditions such as the usage environment and fluid properties of the flow sensor 20 installed in real space, and calculates a virtual flow rate based on the simulation results. As a result, the virtual flow rate calculation device 100 according to this embodiment can highly accurately estimate the actual flow rate measured by the flow sensor 20 in accordance with the user's actual usage environment, usage conditions such as fluid properties, etc. Therefore, the virtual flow rate calculation device 100 according to this embodiment can support the operation of flow rate measurement by the flow sensor 20, which is installed in real space and is affected by usage conditions, and ultimately leads to stable operation of the instrumentation system.

[0090] Furthermore, the virtual flow rate calculation device 100 according to this embodiment may diagnose the flow sensor 20 based on the actual flow rate and the virtual flow rate. In this case, the virtual flow rate calculation device 100 according to this embodiment may issue an alert if the difference between the actual flow rate and the virtual flow rate does not satisfy a standard. As a result, the virtual flow rate calculation device 100 according to this embodiment can diagnose whether the flow sensor 20 itself is functioning correctly or whether the flow sensor 20 is correctly instrumented, depending on whether the calculated virtual flow rate is an intended value in light of the actual flow rate, and if an abnormality is suspected (something unexpected may be happening to the flow sensor 20), the user can be notified of this.

[0091] Furthermore, the virtual flow rate calculation device 100 according to this embodiment may determine the processing to be performed by 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. As a result, the virtual flow rate calculation device 100 according to this embodiment can learn the algorithm for the calculation process so that the calculated virtual flow rate approaches the actual flow rate during a normal period.

[0092] 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 a stress simulation, a fluid simulation, an electromagnetic field simulation, or an ultrasonic simulation, executed in virtual space, preferably a coupled simulation consisting of a combination of these. As a result, the virtual flow rate calculation device 100 according to this embodiment calculates a virtual flow rate based on the results of various simulations, and therefore can calculate a virtual flow rate in accordance with the sensing principle of the flowmeter with high accuracy.

[0093] Here, estimating the flow meter output while taking into account the effects of the operating environment and multiphase conditions requires a high-speed calculation unit and a large-capacity memory, but it has been extremely difficult to provide these inside the flow meter. In contrast, the virtual flow rate calculation device 100 according to this embodiment may be provided by a cloud server. As a result, the virtual flow rate calculation device 100 according to this embodiment makes it possible to remove constraints such as the processing power, memory capacity, and power consumption of a processor installed in a flow meter in real space. Therefore, the virtual flow rate calculation device 100 according to this embodiment increases the amount of data and the degree of freedom in calculation, making it possible to obtain a flow rate output that incorporates various instrumentation conditions of the flow meter.

[0094] 7 shows an example of a block diagram of a virtual flow rate calculation device 100 according to a first modified example, together with the sensor module 10. In the above-described embodiment, the virtual flow rate calculation device 100 executes a simulation each time it calculates a virtual flow rate. However, in this modified example, the virtual flow rate calculation device 100 reuses at least a portion of the simulation results.

[0095] The virtual flow rate calculation device 100 according to this modification further includes a simulation result storage unit 710. In this modification, the simulation unit 140 supplies the simulation result to the calculation unit 150 and the simulation result storage unit 710.

[0096] The simulation result storage unit 710 stores the simulation results. For example, the simulation result storage unit 710 may be a database, and may store the results of the simulation by the simulation unit 140 so that the results can be accessed by the calculation unit 150.

[0097] 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 flow rate.

[0098] The virtual flow rate calculation device 100 according to this modification may store the results of previously executed simulations and reuse at least a portion of those simulation results. As a result, the virtual flow rate calculation device 100 according to this modification stores the results of a previous calculation, eliminating the need to re-simulate under previously executed conditions. This reduces the calculation load and enables analysis that takes multiple conditions into account using a learning calculation module (AI analysis). Furthermore, the virtual flow rate calculation device 100 according to this modification does not necessarily need to perform full-model simulations, including stress, fluid, electromagnetic field, and ultrasonic propagation simulations, in real time. Instead, it stores simulation results under various conditions in advance and recursively obtains simulation results from the stored results, significantly reducing the amount of calculations performed in real time.

[0099] 8 shows an example of a block diagram of a virtual flow rate calculation device 100 according to a second modified example, together with the sensor module 10. In the above-described embodiment, an example was shown in which the virtual flow rate calculation device 100 diagnoses the flow sensor 20 based on a virtual flow rate. However, in this modified example, the virtual flow rate calculation device 100 identifies the fluctuation trend of the virtual flow rate.

[0100] The virtual flow rate calculation device 100 according to this modification further includes a trend identification unit 810, a notification unit 820, and a recommendation unit 830.

[0101] For example, the calculation unit 150 may calculate a virtual flow rate when at least one variable of the environmental information or the physical property information is varied. As an example, the calculation unit 150 may calculate a virtual flow rate when the fluid temperature is varied within a range of ±10°C. The calculation unit 150 may supply the virtual flow rates calculated under different conditions in this way to the trend identification unit 810, along with the conditions under which the virtual flow rates were calculated.

[0102] The trend identification unit 810 can obtain the trend between the varied variable (e.g., fluid temperature) and the virtual flow rate based on the information supplied from the calculation unit 150. In this way, for example, the trend identification unit 810 can identify the trend of the virtual flow rate when at least one variable of the environmental information or the physical property information is varied.

[0103] Here, among the environmental information or physical property information, there are variables that are insensitive to the virtual flow rate, and there are also variables that have a certain trend (for example, a monotonically increasing, a monotonically decreasing, or a trend according to a function). When a variable with a certain trend is found, the trend identification unit 810 may supply information about the trend to the notification unit 820. In this case, the trend identification unit 810 may, for example, derive multiple curves by approximating the data of a scatter plot of the variables and the virtual flow rate in various ways (for example, linear approximation, exponential approximation, logarithmic approximation, polynomial approximation, power approximation, etc.), and select the curve with the largest square of the correlation coefficient (the closer to 1, the stronger the correlation, and the closer to 0, the weaker the correlation) between the data of the scatter plot and each curve as the approximation curve. Furthermore, the trend identification unit 810 may mathematically formulate the selected approximation curve and calculate a correction function from the mathematical formula. The trend identification unit 810 may, for example, supply information indicating such an approximation curve or correction function to the notification unit 820 as information about the trend.

[0104] Then, the notification unit 820 may notify the sensor module 10 of the information relating to the trend via the device-side communication unit 130. In this way, for example, the notification unit 820 can notify the sensor module 10 including the flow sensor 20 of the information relating to the trend.

[0105] Therefore, in this modification, the sensor module 10 may further include a trend characteristic storage unit 50. The trend characteristic storage unit 50 may store information related to the trend notified from the virtual flow rate calculation device 100 as a trend characteristic. Then, the processing unit 30 may process the output signal from the sensor based on the trend characteristic stored in the trend characteristic storage unit 50. As an example, the processing unit 30 may perform correction processing on the output signal from the sensor using a correction function stored in the trend characteristic storage unit 50.

[0106] If there are multiple flow sensors 20 for which the virtual flow rate is to be calculated, the trend identification unit 810 can also identify the trend of the virtual flow rate when at least one variable is varied for each flow sensor 20. Note that such multiple flow sensors 20 may differ from each other in at least one of the supplier and sensing principle. In such a case, the trend identification unit 810 may supply information on each trend identified for each flow sensor 20 to the recommendation unit 830.

[0107] Then, the recommendation unit 830 may determine a flow sensor 20 to recommend from among the plurality of flow sensors 20 based on the tendency of each flow sensor 20. For example, the recommendation unit 830 may compare the magnitude of fluctuations in the virtual flow rate with respect to one or more selected variables (for example, temperature, viscosity, or Reynolds number) between the plurality of 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 modification can compare the fluctuation characteristics of a plurality of flow sensors 20 of various types from various suppliers, and recommend to the user the optimal flow sensor 20 for the usage environment.

[0108] Up to this point, we have explained the fluid to be measured as a single-phase flow. However, in reality, the fluid may contain multiple substances (including unintended substances) resulting in a multi-phase flow.

[0109] Here, "multiphase flow" refers to a fluid in which multiple substances with different physical properties are mixed, and includes, depending on the combination of phases (gas, liquid, and solid), for example, gas-liquid two-phase flow, solid-gas two-phase flow, solid-liquid two-phase flow, and solid-gas-liquid three-phase flow. Furthermore, "multiphase flow" is not necessarily limited to flows with multiple phases, but may also be interpreted as including flows with a single phase, for example, a fluid in which multiple substances that separate like water and oil are mixed, i.e., a liquid-liquid two-phase flow.

[0110] Figure 9 shows an example of a multiphase flow pattern. When a fluid is a single-phase flow, the flow state can be broadly classified as laminar flow or turbulent flow. In contrast, when a fluid is a multiphase flow, various flow states can exist depending on the physical properties of the mixed materials, the flow velocity, the shape of the pipeline, and other factors. Flow patterns are classifications that capture the characteristics of these flow states.

[0111] The upper left of this figure shows a liquid-phase-based dispersed flow. For example, gas (e.g., air bubbles) or solids (e.g., sand or slurry) may flow dispersedly within a fluid that is primarily liquid. Also, other liquids (e.g., droplets) with different physical properties may flow dispersedly without being completely mixed into the primary liquid (e.g., a trace amount of oil dispersed in water, or a trace amount of water dispersed in oil). In this way, a liquid-phase-based dispersed flow can occur when particles such as gas, solids, or liquids flow dispersedly within the liquid phase.

[0112] The upper right of this figure shows a gas-phase-based dispersed flow. For example, solids and liquids may be dispersed and flow within a fluid that is primarily gas. In this way, a gas-phase-based dispersed flow can occur when solid or liquid particles are dispersed and flow within the gas phase.

[0113] The lower left of this figure shows stratified flow in a gas-liquid two-phase flow. For example, in a pipeline extending in a substantially horizontal direction, liquid may flow in the lower layer (bottom layer) of the pipeline, and gas may flow in the upper layer. In this way, stratified flow can occur when multiple components (multiple phases) with different properties flow in layers.

[0114] The lower right of this figure shows an annular flow in a gas-liquid two-phase flow. For example, in a pipeline extending in a nearly vertical direction, the liquid may flow concentrically in the outer layer (on the wall) of the pipeline, and the gas may flow in the inner layer (center) of the pipeline. In this way, an annular flow can occur when multiple components (multiple phases) with different properties flow in a circular pattern.

[0115] As described above, various phase combinations and flow patterns exist in a multiphase flow. When the fluid to be measured becomes a multiphase flow, a mismatch occurs between the actual flow rate measured by the flow sensor 20 and the virtual flow rate due to a decrease or fluctuation in the sensed signal, and the influence of such a mismatch varies depending on the state of the multiphase flow. Therefore, in the second embodiment, the virtual flow rate calculation device 100 also takes into account the multiphase state of the fluid to be measured when calculating the virtual flow rate.

[0116] In the second embodiment, a description of commonalities with the above-described embodiments will be omitted, and only differences will be described, but the virtual flow rate calculation device 100 according to the second embodiment may also be able to provide the same functions as the virtual flow rate calculation device 100 according to the above-described embodiments. Furthermore, the virtual flow rate calculation device 100 according to the second embodiment may also be modified in the same way as the virtual flow rate calculation device 100 according to the above-described embodiments (for example, like the first modified example or the second modified example).

[0117] 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 executes a multiphase fluid simulation. The multiphase fluid simulation unit 145 may simulate a multiphase flow phenomenon in a fluid in a virtual space that reproduces a real space, using environmental information and physical property information. The calculation unit 150 may then calculate a virtual flow rate based on the results of the simulation.

[0118] That is, a virtual flow rate calculation device 100 may be provided that includes an environmental information storage unit 110 that stores environmental information indicating the environment of the real space in which the flow sensor 20 is installed, a physical property information storage unit 120 that stores physical property information indicating the physical properties of the fluid to be measured, a simulation unit 140 that simulates the flow phenomenon of a multiphase flow in the fluid in a virtual space that reproduces the real space using the environmental information and the physical property information, and a calculation unit 150 that calculates a virtual flow rate that estimates the actual flow rate actually measured by the flow sensor 20 based on the simulation results. This virtual flow rate calculation device 100 is also preferably provided by a cloud server, similar to the virtual flow rate calculation device 100 according to the above embodiment.

[0119] In addition, a virtual flow rate calculation method may be provided, which includes a computer storing environmental information indicating the environment of the real space in which the flow sensor 20 is instrumented, storing physical property information indicating the physical properties of the fluid to be measured, simulating the flow phenomenon of a multiphase flow in the fluid in a virtual space that reproduces the real space using the environmental information and the physical property information, and calculating a virtual flow rate that estimates the actual flow rate actually measured by the flow sensor 20 based on the simulated results.

[0120] In addition, a virtual flow rate calculation program may be provided that is executed by a computer and causes the computer to function as an environmental information memory unit 110 that stores environmental information indicating the environment of the real space in which the flow sensor 20 is instrumented, a physical property information memory unit 120 that stores physical property information indicating the physical properties of the fluid to be measured, a simulation unit 140 that uses the environmental information and the physical property information to simulate the flow phenomenon of multiphase flow in the fluid in a virtual space that reproduces the real space, and a calculation unit 150 that calculates a virtual flow rate that estimates the actual flow rate actually measured by the flow sensor 20 based on the simulated results.

[0121] Here, when performing the multiphase fluid simulation, the simulation unit 140 may use an analytical model selected according to at least one of the phase combinations in the multiphase flow and the flow pattern. Such an analytical model may be a physical model of the multiphase flow, such as a continuous phase model or a dispersed phase model. The analytical model may be selected manually, or the simulation unit 140 may automatically select the analytical model according to predetermined rules.

[0122] For example, when a multiphase flow is considered macroscopically and a rough flow is analyzed, 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-like manner.

[0123] On the other hand, when a multiphase flow is viewed at a microscopic level and particles are tracked 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 treated individually in a Lagrangian manner.

[0124] The specific calculation of the virtual flow rate when such a multiphase fluid simulation is performed will be described in detail for each sensing principle of the flow meter.

[0125] FIG. 10 shows an example of a block diagram of a virtual flow rate calculation device 100 according to a second embodiment that functions as a virtual Coriolis flowmeter. In this figure, components having the same functions and configurations as those in FIG. 3 are denoted by the same reference numerals, and descriptions thereof will be omitted hereinafter except for differences. 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 in addition to the fluid simulation unit 141, the stress simulation unit 142, and the electromagnetic field simulation unit 143. In the second embodiment, the virtual flow rate calculation device 100 may perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to estimate the output value of a Coriolis flowmeter used in real space.

[0126] As described above, in a virtual Coriolis flowmeter, the virtual flow rate Q can be calculated from 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 depending on the flow velocity of each phase and its position within the flow tube, and the phase time difference τ also changes accordingly. Therefore, the simulation unit 140 may perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to calculate the flow velocity of each phase within the flow tube and the distribution position of bubbles. Then, the calculation unit 150 may calculate the phase difference φ occurring in the vibration detection sensor from the results of a coupled simulation of the multiphase fluid, stress, and electromagnetic field, and divide this by the excitation frequency fr of the oscillator to calculate the phase time difference τ.

[0127] At this time, the virtual flow rate calculation device 100 estimates the actual flow rate of the Coriolis flowmeter based on the simulation results, and can also estimate various other parameters by performing theoretical calculations using the simulation results.

[0128] 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. As an example, the simulation unit 140 may perform a coupled simulation of a multiphase fluid and stress. The calculation unit 150 may calculate the resonant frequency fv of the entire flow tube including the fluid from the results of this simulation. The calculation unit 150 may then estimate the fluid density ρ using the following equation. That is, the calculation unit 150 may estimate the fluid density ρ by multiplying the squared value of the resonant frequency fv of the flow tube in a vacuum by the resonant frequency fv of the entire flow tube including the fluid, by a coefficient C.

number

[0129] The 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 gas phase and the resonant frequency fref1 of the flow tube when the fluid is solely liquid phase are stored in advance. In this case, the calculation unit 150 may estimate the fraction of gas 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. In this way, when the flow sensor 20 is a Coriolis flowmeter, the calculation unit 150 may estimate at least one of the density of the fluid and the fraction of multiphase flow based on the resonant frequency of the flow tube.

[0130] In a Coriolis flowmeter, the flow tube is vibrated by the excitation force of the oscillator. For example, if the liquid contains bubbles, the damping of the flow tube increases, and the drive current applied to the oscillator increases to compensate for the excitation. Therefore, the virtual flow rate calculation device 100 can estimate the multiphase flow fraction based on the drive current. For example, the simulation unit 140 may perform a coupled simulation of multiphase fluid, stress, and electromagnetic fields. The calculation unit 150 may calculate the drive current applied to the oscillator from the results of this simulation. Assume that a data set showing 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 may estimate the gas fraction in the liquid by comparing the calculated drive current with a known data set. Thus, when the flow sensor 20 is a Coriolis flowmeter, the calculation unit 150 may estimate the multiphase flow fraction based on the drive current applied to the oscillator to vibrate the flow tube.

[0131] The calculation unit 150 may notify the diagnosis unit 160 of the parameters estimated in this manner, for example. The diagnosis unit 160 may then issue an alert if the parameters notified from the calculation unit 150 do not satisfy a predetermined criterion. As an example, assume that a certain amount of contaminants is known to be mixed into a fluid in a plant process. In this case, the diagnosis unit 160 may issue an alert if the parameters notified from the calculation unit 150 (e.g., fluid density, multiphase flow fraction, etc.) exceed a range expected from the known amount of contaminants. The diagnosis unit 160 can issue an alert if, for example, the parameters estimated by the calculation unit 150 in this manner do not satisfy a predetermined criterion. Note that, in the second embodiment, the diagnosis unit 160 may also have the functions described in the above embodiments. That is, the diagnosis unit 160 can also issue an alert if the difference between the actual flow rate and the virtual flow rate does not satisfy a predetermined criterion.

[0132] 11 shows an example of a block diagram of a virtual flow rate calculation device 100 according to a second embodiment that functions as a virtual ultrasonic flowmeter. In this figure, the same reference numerals are used to designate components having the same functions and configurations as those in FIG. 4, and descriptions thereof will be omitted hereinafter except for differences. 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 in addition to the fluid simulation unit 141 and the ultrasonic propagation simulation unit 144. In the second embodiment, the virtual flow rate calculation device 100 may perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to estimate the output value of an ultrasonic flowmeter used in real space.

[0133] As described above, in a virtual ultrasonic flowmeter, the virtual flow rate Q can be calculated from the propagation times t1 and t2 of ultrasonic waves. However, for example, if the fluid to be measured is a dispersed flow in which particles such as bubbles or solids are dispersed in the liquid phase, the particles cause scattering and reflection of ultrasonic waves. This can reduce the signal strength of the ultrasonic waves transmitted from the ultrasonic transmitter and receive it at the opposite side, or change the apparent propagation velocity in the liquid. Therefore, the simulation unit 140 may perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to calculate the flow velocity distribution in the pipe. The calculation unit 150 may then calculate the propagation times t1 and t2 from the results of a coupled simulation of the multiphase fluid and ultrasonic waves.

[0134] In this case, the virtual flow rate calculation device 100 estimates 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. The virtual flow rate calculation device 100 can also diagnose the amount of bubbles and solid particles and estimate the impact on the flow rate output.

[0135] For example, the size (diameter) of particles such as bubbles and solids affects the magnitude and frequency components of scattered reflections. Therefore, the calculation unit 150 may analyze the received signal strength of the ultrasonic waves for each frequency band and combine the analysis results with the simulation results of ultrasonic propagation and multiphase fluid to estimate the particle distribution state (size, etc.). This allows the virtual flow rate calculation device 100 to diagnose fluid changes, etc. based on the particle distribution state. In this way, when the flow sensor 20 is an ultrasonic flowmeter, the calculation unit 150 may estimate the distribution state of particles dispersed in the fluid based on the results of analyzing the received signal strength of the ultrasonic waves for each frequency band.

[0136] Furthermore, when particles such as bubbles or solids flow unevenly, a difference occurs in the received signal strength of opposing ultrasonic waves (i.e., the received signal strength of ultrasonic waves from the upstream side to the downstream side and the received signal strength of ultrasonic waves from the downstream side to the upstream side). Therefore, the calculation unit 150 may calculate the difference in the received signal strength of the opposing ultrasonic waves, i.e., the degree of imbalance. Here, it is assumed that a data set showing the correlation between the difference in received signal strength and the uneven distribution state of particles is stored in advance. In this case, the calculation unit 150 may estimate the uneven distribution state of particles such as bubbles or solids by comparing the calculated difference in received signal strength with a known data set. In this way, when the flow sensor 20 is an ultrasonic flowmeter, the calculation unit 150 may estimate the uneven distribution state of particles dispersed in the fluid based on the difference in the received signal strength of opposing ultrasonic waves.

[0137] The calculation unit 150 may notify the diagnosis unit 160 of the parameters estimated in this manner, for example. Then, the diagnosis unit 160 may issue an alert if the parameters notified from the calculation unit 150 do not satisfy a predetermined standard. As an example, the diagnosis unit 160 may monitor the parameters notified from the calculation unit 150 (e.g., particle distribution state, particle uneven distribution state, etc.), and issue an alert if the fluctuation value of the parameter exceeds a predetermined range. The diagnosis unit 160 can issue an alert, for example, if the parameters estimated by the calculation unit 150 in this manner do not satisfy a predetermined standard.

[0138] FIG. 12 shows an example block diagram of a virtual flow rate calculation device 100 according to a second embodiment that functions as a virtual electromagnetic flowmeter. In this figure, components having the same functions and configurations as those in FIG. 5 are denoted by the same reference numerals, and descriptions thereof will be omitted hereinafter except for differences. 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 in addition to the fluid simulation unit 141 and the electromagnetic field simulation unit 143. In the second embodiment, the virtual flow rate calculation device 100 may perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to estimate the output value of an electromagnetic flowmeter used in real space.

[0139] As described above, in a virtual electromagnetic flowmeter, the virtual flow rate Q can be calculated from the electromotive force e generated at 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, if the fluid to be measured is a dispersed flow in which electrically insulating particles (such as air bubbles, oil, sand, or slurry) are dispersed in an electrically conductive liquid phase (e.g., water), the electrically insulating particles do not contribute to the electromotive force detected by the electrodes. Therefore, the simulation unit 140 may perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to calculate the occurrence frequency and area of ​​particles near the electrodes. The calculation unit 150 may then calculate the electromotive force e by incorporating signals from areas where particles are present into the integral calculation as zero. Naturally, since there are elements omitted in the simulation, the calculation unit 150 may incorporate a predetermined coefficient that preliminarily correlates the simulation results with the actual flow rate. 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 dispersed in the fluid to be measured.

[0140] At this time, the virtual flow rate calculation device 100 estimates the actual flow rate of the electromagnetic flow meter based on the simulation results, and can also estimate various other parameters by performing theoretical calculations using the simulation results.

[0141] For example, electrically insulating particles rubbing against the electrodes can generate fluctuating electrical noise. Various flow noises can also occur in the electrodes of an electromagnetic flowmeter depending on various fluid conditions. Such flow noises can be as described in Japanese Patent No. 6229852, and therefore will not be described here. In the second embodiment, the simulation unit 140 includes a multiphase fluid simulation unit 145, enabling the virtual flow calculation device 100 to correlate such flow noises generated in the electrodes of the electromagnetic flowmeter. For example, by determining the flow fluctuations and fluctuations of the multiphase flow near the electrodes, the calculation unit 150 can calculate the amount of fluctuation in the multiphase flow fraction at the measurement cross section of the measuring pipe or near the electrodes. By pre-correlating these calculation results with the actual flow rate of the electromagnetic flowmeter and setting a predetermined coefficient, it becomes possible to correlate the simulation results in virtual space with the flow noise diagnostic signal. This allows the calculation unit 150 to identify the electromotive force effect of the electrically insulating material in the dispersed phase and the amount of flow noise obtained from the multiphase fluid simulation. In this way, when the flow sensor 20 is an electromagnetic flowmeter, the calculation unit 150 may estimate the amount of flow noise generated at the electrodes based on the electromotive force effect of electrical insulators dispersed in the fluid.

[0142] Furthermore, the calculation unit 150 can estimate the multiphase state by comparing the fluctuations in the process value of the electromagnetic flowmeter and the fluctuations in the flow noise with the results of parametrically calculating the multiphase state, thereby determining the bubble fraction when the dispersed phase is a gas phase, or the oil fraction when the dispersed phase is oil. In this way, when the flow sensor 20 is an electromagnetic flowmeter, the calculation unit 150 may estimate the fraction of the multiphase flow based on the results of parametrically calculating the simulated results.

[0143] The calculation unit 150 may notify the diagnosis unit 160 of the parameters estimated in this manner, for example. Then, the diagnosis unit 160 may issue an alert if the parameters notified from the calculation unit 150 do not satisfy a predetermined criterion. As an example, the diagnosis unit 160 may monitor the parameters notified from the calculation unit 150 (for example, the amount or fraction of flow noise), and issue an alert if the fluctuation value of the parameter exceeds a predetermined range. The diagnosis unit 160 can issue an alert, for example, if the parameters estimated by the calculation unit 150 in this manner do not satisfy a predetermined criterion.

[0144] FIG. 13 shows an example of a block diagram of a virtual flow rate calculation device 100 according to a second embodiment that functions as a virtual vortex flowmeter. In this figure, components having the same functions and configurations as those in FIG. 6 are denoted by the same reference numerals, and descriptions thereof will be omitted hereinafter except for differences. In the virtual flow rate calculation device 100 according to the second embodiment, 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 addition to the fluid simulation unit 141. In the second embodiment, the virtual flow rate calculation device 100 may perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to estimate the output value of a vortex flowmeter used in real space.

[0145] 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, when the fluid to be measured is in a gas-liquid multiphase state such as a stratified flow or annular flow, the presence of a liquid phase on the pipe wall reduces the apparent pipe inner diameter and increases the flow velocity. Therefore, the simulation unit 140 may perform a multiphase fluid simulation using the multiphase fluid simulation unit 145 to calculate the flow velocity distribution in the pipe. Then, the calculation unit 150 may calculate the virtual flow rate Q of the gas phase alone from the results of the simulation.

[0146] In this case, the virtual flow rate calculation device 100 estimates the actual flow rate of the vortex flowmeter based on the simulation results, and can also estimate various other parameters by performing theoretical calculations using the simulation results. The virtual flow rate calculation device 100 can also be used to estimate the dryness fraction during a steam process.

[0147] For example, the virtual flow rate calculation device 100 can estimate the fraction of multiphase flow from the amplitude of the voltage generated in the piezoelectric element. As an example, to detect the vortex frequency f, a method is employed in which a piezoelectric element detects the stress generated by the alternating pressure applied to the vortex shedder when Kármán vortices are generated. However, if a liquid phase is present on the pipe wall, the alternating pressure applied to the vortex shedder due to the generation of Kármán vortices is lower than that in the case of a gas phase alone. Therefore, the simulation unit 140 may perform a coupled simulation of the multiphase fluid and stress. The calculation unit 150 may calculate the amplitude of the voltage generated in the piezoelectric element using the simulation results and a piezoelectric function, and estimate the liquid fraction in the gas phase from the amplitude. In this way, when the flow sensor 20 is a vortex flowmeter, the calculation unit 150 may estimate the fraction of multiphase flow based on the amplitude of the voltage generated in the piezoelectric element.

[0148] The virtual flow rate calculation device 100 can also estimate the fraction of multiphase flow from noise (fluctuations or fluctuations in the flow of the multiphase fluid) generated in the piezoelectric element. For example, if a liquid phase is present on the pipe wall, the piezoelectric element in the vortex shedder detects vibrations caused by fluctuations in the liquid flow as noise. Furthermore, if droplets are present in the gas phase, the collision of the droplets with the vortex shedder generates noise in the piezoelectric element. Therefore, the simulation unit 140 may perform a coupled simulation of the multiphase fluid, stress, and electromagnetic field. The calculation unit 150 may calculate the noise generated in the piezoelectric element based on the results of this simulation and estimate the liquid fraction in the gas phase, etc., from the noise. In this way, when the flow sensor 20 is a vortex flowmeter, the calculation unit 150 may estimate the fraction of multiphase flow based on the noise generated in the piezoelectric element.

[0149] Furthermore, the simulation unit 140 may use the fraction of the multiphase flow (for example, the fraction of the gas and liquid phases) to perform a multiphase fluid simulation using the multiphase fluid simulation unit 145, and calculate the flow velocity distribution in the pipeline. Then, the calculation unit 150 may calculate the virtual flow rate Q of the gas phase alone from the results of the simulation. In this way, when the fluid is in a multiphase state of two phases, gas and liquid, the calculation unit 150 may calculate the virtual flow rate Q of the gas phase alone based on the fraction of the multiphase flow.

[0150] The calculation unit 150 may notify the diagnosis unit 160 of the parameters estimated in this manner, for example. Then, the diagnosis unit 160 may issue an alert if the parameters notified from the calculation unit 150 do not satisfy a predetermined criterion. 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 alert if the fluctuation value of the parameter exceeds a predetermined range. The diagnosis unit 160 can issue an alert, for example, if the parameters estimated by the calculation unit 150 in this manner do not satisfy a predetermined criterion.

[0151] Thus, 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.

[0152] In flow rate measurement, the multiphase state inside the measuring pipe affects measurement accuracy. Therefore, the virtual flow rate calculation device 100 according to the second embodiment uses environmental information and physical property information to simulate the flow phenomenon of a multiphase flow in the fluid to be measured, and calculates a virtual flow rate based on the simulation results. As a result, the virtual flow rate calculation device 100 according to the second embodiment can further enhance the versatility of flow rate measurements and diagnosis related to flow rate measurements.

[0153] Furthermore, the virtual flow rate calculation device 100 according to the second embodiment can estimate not only the actual flow rate but also various other parameters in accordance with the sensing principle of a flow meter, and can also issue an alert if the estimated parameters do not satisfy predetermined standards. Furthermore, when performing a multiphase fluid simulation, the virtual flow rate calculation device 100 according to the second embodiment can use the optimal analysis model depending on the multiphase state, such as using a continuous phase model to reduce the calculation load when analyzing a rough flow, or using a dispersed phase model to obtain detailed simulation results when tracking individual particles.

[0154] Various embodiments of the present invention may be described with reference to flowcharts and block diagrams, where the blocks may represent (1) stages of a process in which operations are performed or (2) sections of an apparatus responsible for performing the operations. Particular stages and sections may be implemented by dedicated circuitry, programmable circuitry provided with computer-readable instructions stored on a computer-readable medium, and / or a processor provided with computer-readable instructions stored on a computer-readable medium. Dedicated circuitry may include digital and / or analog hardware circuitry, and may include integrated circuits (ICs) and / or discrete circuits. Programmable circuitry may include reconfigurable hardware circuitry, including logical AND, OR, XOR, NAND, NOR, and other logical operations, flip-flops, registers, memory elements such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), and the like.

[0155] A computer-readable medium may include any tangible device capable of storing instructions that are executed by an appropriate device, such that the computer-readable medium having instructions stored thereon comprises an article of manufacture containing instructions that can be executed to create means for performing the operations specified in the flowcharts or block diagrams. Examples of computer-readable media may include electronic, magnetic, optical, electromagnetic, and semiconductor storage media. More specific examples of computer-readable media may include floppy disks, diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), electrically erasable programmable read-only memory (EEPROM), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital versatile disc (DVD), Blu-ray (RTM) disc, memory stick, integrated circuit card, and the like.

[0156] The computer readable instructions may include either assembler instructions, Instruction Set Architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages.

[0157] The computer-readable instructions may be provided to a processor or programmable circuitry of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, either locally or over a wide-area network (WAN) such as a local area network (LAN), the Internet, etc., which executes the computer-readable instructions to create means for performing the operations specified in the flowcharts or block diagrams. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0158] 14 illustrates an example of a computer 9900 in which aspects of the present invention may be embodied, in whole or in part. Programs installed on the computer 9900 may cause the computer 9900 to function as or perform operations associated with an apparatus or one or more sections of the apparatus according to embodiments of the present invention, and / or to perform a process or steps of a process according to embodiments of the present invention. Such programs may be executed by the CPU 9912 to cause the computer 9900 to perform specific operations associated with some or all of the blocks in the flowcharts and block diagrams described herein.

[0159] The computer 9900 according to this embodiment includes a CPU 9912, a RAM 9914, a graphics controller 9916, and a display device 9918, which are interconnected by a host 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 host controller 9910 via an input / output controller 9920. The computer also includes legacy 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.

[0160] The CPU 9912 operates according to programs stored in the ROM 9930 and RAM 9914, thereby controlling each unit. The graphics controller 9916 retrieves image data generated by the CPU 9912 into a frame buffer or the like provided in the RAM 9914 or into the graphics controller itself, and causes the image data to be displayed on the display device 9918.

[0161] 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 in 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.

[0162] The ROM 9930 stores therein a boot program or the like that is executed by the computer 9900 upon activation, and / or programs that depend on the hardware of the computer 9900. The input / output chip 9940 may 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, etc.

[0163] The programs are provided by a computer-readable medium such as a DVD-ROM 9901 or an IC card. The programs are 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 by the computer 9900, and causes cooperation between the programs and the various types of hardware resources described above. An apparatus or method may be configured by implementing information manipulation or processing in accordance with the use of the computer 9900.

[0164] For example, when communication is performed between the computer 9900 and an external device, the CPU 9912 may execute a communication program loaded into the RAM 9914 and instruct the communication interface 9922 to perform 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 processing area provided in the RAM 9914, the hard disk drive 9924, the DVD-ROM 9901, or a recording medium such as an IC card, and transmits the read transmission data to the network, or writes received data received from the network to a reception buffer processing area or the like provided on the recording medium.

[0165] The CPU 9912 may also cause all or a necessary portion of a file or database stored on an external recording medium such as a hard disk drive 9924, a DVD drive 9926 (DVD-ROM 9901), an IC card, etc. to be read into the RAM 9914, and perform various types of processing on the data on the RAM 9914. The CPU 9912 then writes back the processed data to the external recording medium.

[0166] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and subjected to information processing. The CPU 9912 may perform various types of processing on data read from the RAM 9914, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequences of the programs, and write the results back to the RAM 9914. The CPU 9912 may also search for information in a file, database, etc. on the recording medium. For example, if multiple entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored on the recording medium, the CPU 9912 may search for an entry that matches a condition specified by the attribute value of the first attribute from among the multiple entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0167] The programs or software modules described above may be stored in a computer-readable medium on or near the computer 9900. A recording medium such as a hard disk or RAM provided in a server system connected to a dedicated communication network or the Internet can also be used as a computer-readable medium, thereby providing the programs to the computer 9900 via the network.

[0168] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the claims that such modifications and improvements can also be included within the technical scope of the present invention.

[0169] It should be noted that the execution order of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and that the processes can be performed in any order unless the output of a previous process is used in a subsequent process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, this does not mean that the processes must be performed in this order. [Explanation of symbols]

[0170] 10 Sensor Module 20 Flow Sensor 30 Processing section 40 Sensor side communication unit 50 Trend characteristics memory section 100 Virtual flow rate calculation device 110 Environmental information storage unit 120 Physical property information storage section 130 Device side communication unit 140 Simulation Department 141 Fluid Simulation Department 142 Stress Simulation Section 143 Electromagnetic Field Simulation Department 144 Ultrasonic Propagation Simulation Department 145 Multiphase Fluid Simulation Department 150 Arithmetic section 160 Diagnostic Department 710 Simulation result storage unit 810 Trend Identification Department 820 Notification Department 830 Recommendation Section 9900 Computer 9901 DVD-ROM 9910 Host Controller 9912 CPU 9914 RAM 9916 Graphics Controller 9918 Display Device 9920 Input / Output Controller 9922 Communication Interface 9924 Hard Disk Drive 9926 DVD drive 9930 ROM 9940 I / O chip 9942 keyboard

Claims

1. an environmental information storage unit that stores environmental information indicating an environment of a real space in which the flow sensor is installed; a property information storage unit that stores property information indicating the 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 that reproduces the real space using the environmental information and the physical property information; a calculation unit that calculates a virtual flow rate by estimating the actual flow rate actually measured by the flow rate sensor based on the simulation result; A virtual flow rate calculation device comprising:

2. 2. The virtual flow rate calculation device according to claim 1, wherein the flow rate sensor is at least one of a Coriolis flow meter, an ultrasonic flow meter, an electromagnetic flow meter, and a vortex flow meter.

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

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

5. the flow sensor is the ultrasonic flow meter; 3. The virtual flow rate calculation device according to claim 2, wherein the calculation unit estimates the distribution state of particles dispersed in the fluid based on a result of analyzing the received signal strength of the ultrasonic waves for each frequency band.

6. the flow sensor is the ultrasonic flow meter; The virtual flow rate calculation device according to claim 2 , wherein the calculation unit estimates the uneven distribution state of particles dispersed in the fluid based on a difference in received signal strength of opposing ultrasonic waves.

7. the flow sensor is an electromagnetic flow meter; 3. The virtual flow rate calculation device according to claim 2, wherein the calculation unit estimates the amount of flow noise generated at the electrodes based on the electromotive force effect of an electrical insulator dispersed in the fluid.

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

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

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

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

12. The virtual flow rate calculation device according to claim 3 , further comprising a diagnosis unit that issues an alert when the parameter estimated by the calculation unit does not satisfy a predetermined standard.

13. The virtual flow rate calculation device according to claim 12 , wherein the diagnosing unit further issues an alert when the difference between the actual flow rate and the virtual flow rate does not satisfy a predetermined standard.

14. The virtual flow rate calculation device according to claim 1 , wherein the simulation unit uses an analytical model selected according to at least one of a combination of phases in the multiphase flow and a flow pattern.

15. The virtual flow rate calculation device according to claim 14 , wherein the analytical model is a continuous phase model or a dispersed phase model.

16. The virtual flow rate calculation device according to claim 1 , which is provided by a cloud server.

17. The computer storing environmental information indicative of an environment of a real space in which the flow sensor is instrumented; storing physical property information indicating the physical properties of the fluid to be measured; simulating a flow phenomenon of a multiphase flow in the fluid in a virtual space that reproduces the real space using the environmental information and the physical property information; Calculating a virtual flow rate that estimates the actual flow rate actually measured by the flow sensor based on the simulation result; A virtual flow rate calculation method comprising:

18. The method is executed by a computer, causing the computer to: an environmental information storage unit that stores environmental information indicating an environment of a real space in which the flow sensor is installed; a property information storage unit that stores property information indicating the 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 that reproduces the real space using the environmental information and the physical property information; a calculation unit that calculates a virtual flow rate by estimating the actual flow rate actually measured by the flow rate sensor based on the simulation result; This is a virtual flow calculation program that functions as a virtual flow rate calculation program.

Images