KR20240094518A - Low flow rate flow measurement system and method - Google Patents

Abstract

An embodiment of the present invention includes a flow sensor unit that measures either the flow rate or the water level within the pipe and a controller that calculates the flow rate by filtering the raw data received from the flow sensor unit, and the controller has a speed of 0.3 m/sec or less. When the flow rate is detected, the bandwidth and moving average time of the noise filter are adjusted to calculate the flow rate value using the effective data calculated after noise filtering.

Description

Low flow rate flow measurement system and method}

The present invention relates to a low flow rate flow measurement system and method capable of measuring flow rate even at low flow rates.

In general, an electromagnetic flowmeter is known as a method of measuring the flow rate of fluid flowing in a pipe, and is a flow measurement method that applies Faraday's law, which states that electromotive force is generated in proportion to the flow rate when a conductive fluid passes through a magnetic field.

The signal detected by the electromagnetic flow meter is generated directly in proportion to the volumetric flow rate, has a wide measurement range, and in the case of conductive fluids, has the advantage of being able to measure the flow rate regardless of temperature, pressure, density, viscosity, conductivity, etc. there is.

To explain this simply, a coil is used to form a magnetic field in the direction perpendicular to the fluid flowing through the pipe, and when the fluid passes through the magnetic field, a voltage difference is generated at the electrode in the direction perpendicular to the coil, and the magnitude of this voltage is proportional to the flow rate. Flow rate can be measured.

Due to the characteristics of these electromagnetic flowmeters, they measure the average flow velocity as the viscosity increases on the wall inside the pipe in the laminar flow and transition section at the point when the pipe through which the fluid flows is straight or changes from turbulent flow to the transition section in the section below 0.6m/sec. Noise occurs in the raw data itself.

This kind of noise is generated more severely when the flow speed is slow, and there is a problem that accurate flow measurement is difficult because so much noise is generated that it is difficult to extract valid data below 0.3 m/sec.

KR 10-1573680 B1(2015.11.26)

The present invention was created to solve the conventional problems, and the purpose of the present invention is to provide a flow measurement system and method capable of measuring at low flow rates that can accurately measure the flow rate in a full or empty pipe of 0.3 m/sec or less. there is.

The present invention may include the following examples to achieve the above object.

An embodiment of the present invention includes a flow sensor unit that measures the flow rate within the pipe and a controller that calculates the flow rate by filtering the raw data received from the flow sensor unit, and the controller adjusts the bandwidth of the noise filter when flow in the transition section is detected. It is characterized by calculating the flow rate value using the effective data calculated after noise filtering by adjusting the moving average time.

In addition, the present invention, as another embodiment, includes a flow sensor unit that measures either the flow rate or water level in the pipe and a controller that calculates the flow rate by filtering the raw data received from the flow sensor unit, and the controller calculates the Reynolds index value. If is calculated and is greater than the set value, the flow rate value can be calculated after going through the noise removal filtering process by adjusting the bandwidth and moving average time of the noise filter.

In the above embodiments, the controller includes a sensor control unit that controls the power supply and driving current of the flow sensor unit, a receiver that receives data, and a method for calculating the Reynolds index using at least one parameter of the diameter of the pipe, temperature, and flow rate. An index calculation module, a filter control module that adjusts the bandwidth and moving average time of the noise filter when the index value calculated from the index calculation module corresponds to the set standard value, and an output module that calculates the flow rate value as valid data filtered by the noise filter. It can be included.

In the above embodiment, the controller may further include a storage device for storing data.

Additionally, the noise filter can secondarily filter the raw data according to the Reynolds index value calculated after the first filtering.

Another embodiment of the present invention includes the step of detecting one or more of the water level and the flow rate in the flow sensor unit and the step of calculating the flow rate in the controller through the data sensed by the flow sensor unit, and the step of calculating the flow rate in the controller is performed using raw data. A first step of noise filtering, a step of calculating the Reynolds exponent value and detecting the threshold, a step of adjusting the bandwidth and moving average time of the noise filter if the Reynolds exponent value corresponds to the threshold, and a second step of noise filtering to remove the noise. It provides a low-flow rate flow measurement method including the step of removing and calculating the flow rate from data extracted after secondary noise filtering.

In the above example, the Reynolds exponent value may be 4000.

The present invention can accurately measure the flow rate of a pipe at a flow rate of 0.3 m/sec or less, allowing accurate data to be calculated from various measurements such as pipe damage, abnormal situations, and life prediction.

1 is a block diagram showing a controller in the present invention.
Figure 2 is a flow chart showing a low flow rate flow measurement method.
Figure 3 is a flowchart showing step S200.
Figure 4 is a schematic diagram illustrating the noise filtering process.
Figures 5 and 6 are data comparing embodiments of the present invention.

Although the present invention may be subject to various changes and may have various embodiments, specific embodiments will be described in detail by illustrating them in the drawings. This is not intended to limit the present invention to specific embodiments, and is not intended to limit the present invention to any of the changes, equivalents, or substitutes included in the spirit and scope of the present invention for connecting and/or fixing structures extending in different directions. It must be understood as applicable.

The terms used in this specification are merely used to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly dictates otherwise.

In this specification, terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that this does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

In this specification, an empty pipe refers to a pipe through which water flows while there is an empty space when water flows within the pipe, and a full pipe refers to a pipe through which water flows without an empty space within the pipe.

Hereinafter, preferred embodiments of the low flow rate flow measurement system and method according to the present invention will be described with reference to the accompanying drawings.

1 is a block diagram showing a controller in the present invention.

Referring to FIG. 1, the present invention includes a flow rate sensor unit 10 and a controller 20 that measures flow rate through raw data of the flow sensor unit 10.

The flow sensor unit 10 is fixed to the lower part of the pipe and outputs raw data detecting the water level and average flow rate in the obesity pipe to the controller 20 by fusing ultrasonic waves and electromagnets. For this purpose, the flow sensor unit 10 may be equipped with an ultrasonic module (not shown) that outputs ultrasonic waves and an electromagnet module (not shown) that generates electromotive force.

Among them, the electromagnet module (not shown) is, for example, between an electrode and an excitation coil that measures the flow rate within the obesity tube and a pair of electrodes drawn from mutually opposing positions on the upper surface of the housing and is excited on the inside. It may include a radiation prevention unit (not shown) to which the coil is fixed.

In particular, when measuring a non-obese tube, it is desirable that the upper surface of the housing from which the electrode is drawn is formed on a straight horizontal surface after forming an inclined surface at the tip to reduce resistance to water in the tube.

Additionally, the ultrasonic module (not shown) can measure the water level by outputting ultrasonic waves within the obesity tube and receiving ultrasonic waves reflected from the water surface.

The configuration of the flow sensor unit 10 as described above is an example of one of various functions and configurations and does not limit the present invention. The controller 20 controls the flow sensor unit 10 to receive the detected flow rate and water level (H) detection signal (raw data) and calculates and outputs the flow rate. Here, the controller 20 calculates the flow rate by performing signal amplification, noise removal, signal conversion, and calculation processing to extract valid data from the raw data.

To be more specific, the controller 20 includes a receiving unit 210 that receives data from the flow sensor unit 10, a sensor control unit 280 that controls the flow sensor unit 10, and amplifies and signals the raw data. A flow measurement module 220 that processes and measures the flow rate, an index calculation module 230 that calculates a standard index, a noise filter 260 that removes noise from raw data, and the bandwidth and time of the noise filter 260. It includes a filter control module 240 that adjusts and an output module 250 that calculates and outputs the flow rate through the flow rate.

In addition, the controller 20 may further include a device for signal amplification and conversion (analog signal to digital signal), the description of which is omitted as generally known devices and/or methods are applied.

Additionally, the controller 20 may include a storage device 270 that stores at least one of raw data, filtered valid data, and a result value calculated using the valid data. Here, the storage device 270 may include a connection device (for example, a USB connector) capable of connecting an external terminal.

In addition, the controller 20 can be divided into two CPUs to play a role in controlling flow rate calculation and noise filtering. For example, the above-described flow rate measurement module 220 is implemented through the first CPU (MC), and the index calculation module 230, filter control module 240, and output module 250 are implemented through the second CPU (SC). . This classification of CPU roles is effective in that it can improve calculation speed and prevent errors during operation compared to when operating with a single CPU.

The receiving unit 210 may receive data from the flow sensor unit 10.

The sensor control unit 280 controls the power supply and driving current of the flow sensor unit.

The flow velocity measurement module 220 calculates the flow velocity within the pipe as valid data filtered by the noise filter 260. As the flow rate calculation algorithm applies what is generally known, its description is omitted.

The index calculation module 230 calculates the Reynolds index through the pipe diameter, temperature, and/or flow rate. For example, if the flow speed in the pipe is less than 0.3 m/sec and it enters a transition section rather than a completely turbulent flow area, a lot of noise is generated due to the influence of viscosity near the inner surface of the pipe. Therefore, conventionally, it is known that flow rate measurement is difficult due to the generation of invalid noise at flow speeds of 0.3 m/sec or less.

However, in order to enable flow rate measurement even at flow rates of 0.3 m/sec or less, the present invention sets a threshold to distinguish between low flow rates and higher flow rates.

As a result of the measurement, the Reynolds index was found to output regular values depending on the flow rate, and through this, the Reynolds index of 4000 or less was set as the threshold.

The filter control module 240 adjusts the bandwidth and time of the noise filter 260. For example, if the Reynolds index calculated after the primary noise filter 260 is 4000 or less, the filter control module 240 adjusts the bandwidth and time of the noise filter 260 to perform secondary filtering. Control.

At this time, the noise filter 260 will be described with reference to FIG. 4. Figure 4 is a graph showing an example of the secondary filtering process of the noise filter 260.

Referring to FIG. 4, the noise filter 260 uses a moving average technique to distinguish valid data from invalid data (noise). Additionally, the noise filter 260 may perform secondary filtering when the Reynolds index is 4000 or less and/or a flow velocity of 0.3 m/sec or less is detected after primary filtering.

At this time, the filter control module 240 adjusts the bandwidth and time of the noise filter 260 by lowering the upper limit (Ho) of the bandwidth of the noise filter 260, increasing the lower limit (Lo), and shortening or extending the moving average time. Adjust.

For example, when a lot of normal data is distributed within the set primary band, the filter control module 240 adjusts the moving average time to be longer and performs primary filtering.

In addition, the filter control module 240 adjusts the bandwidth to the set secondary band when the Reynolds index value set after the first filtering corresponds to the threshold (4000 or less) and configures the noise filter 260 to shorten the moving average time. Control to distinguish between valid data and noise within a narrower range.

In the present invention, a dead zone flow measurement error test was conducted through an example in which this method was applied and a comparative example in which the method was not applied, and results such as the graph in FIG. 5 and the table in FIG. 6 were obtained.

Figure 5 is a comparison graph, and Figure 6 is a table listing measured values.

Referring to Figures 5 and 6, in the case where the present invention was applied (our company), it was measured from -0.22 to -0.1 at 0.3 m/sec or less, and in the case of the comparative example (other company), it was measured from 1.61 to 0.21. In other words, the present invention performs noise filtering using the moving average technique at a flow speed of 0.3 m/sec or less, but after adjusting the bandwidth and moving average time during the second filtering according to the Reynolds index value calculated after the first filtering. When secondary filtering was performed, it was confirmed that a much more stable range of values could be calculated than in the comparative example.

The output module 250 calculates the flow rate value through filtered data. Here, the output module 250 can store the calculated flow rate value in the storage device 270 or output it to a display (not shown).

The present invention can provide a low flow rate flow measurement method through the above configuration. This is explained with reference to FIGS. 2 and 3.

Figure 2 is a flow chart showing a low flow rate flow measurement method according to the present invention.

Referring to FIG. 2, the present invention includes a step S100 in which the flow sensor unit 10 transmits raw data detecting the flow rate, a step S200 in which the controller 20 filters noise and calculates a flow rate value with valid data, and the controller 20. (20) may include step S300 of storing the calculated data in the storage device 270 and transmitting it to an external terminal.

Step S100 is a step in which the flow sensor unit 10 detects the water level and/or flow rate within the pipe and transmits data to the controller 20. The flow sensor unit 10 transmits data measuring the water level and/or flow rate within the pipe by being turned on or automatically set under the control of the controller 20. At this time, the ultrasonic module (not shown) outputs ultrasonic waves, and the excitation coil is excited to generate electromotive force between electrodes protruding from both sides of the upper surface of the housing of the flow sensor unit 10 to measure the flow rate. The data measured in this way (raw data) is transmitted to the receiving unit of the controller 20.

Step S200 is a step in which the controller 20 amplifies, removes noise, and converts the raw data of the flow sensor unit 10 into a digital signal to calculate effective data, and calculates the water level and/or flow rate through the effective data. .

Here, the controller 20 may perform a secondary noise filtering process to resolve difficulties in measuring flow rate due to noise generation at flow speeds of 0.3 m/sec or less. This will be described later with reference to FIG. 3.

Step S300 is a step in which the controller 20 stores valid data and flow rate values from which noise has been removed in the storage device 270 and transmits the data upon request from an external terminal. The controller 20 may output the result calculated in step S200 to a display (not shown) and store it in the storage device 270. And when a connection is requested through the receiver 210 or a wired connector such as USB, the controller 20 may grant the connection or transmit the requested data after verifying identification information (eg, ID and password).

Figure 3 is a flowchart showing step S200.

Referring to Figure 3, step S200 includes a step S210 of receiving raw data, a step S220 of primary noise filtering, a step S230 of calculating the Reynolds index, a step S240 of detecting a value above the reference value, and a noise filter if the value is above the reference value. It includes a step S250 of adjusting (260), a step S260 of secondary noise filtering, and a step S270 of calculating the flow rate value.

Step S210 is a step in which the controller 20 receives data from the flow sensor unit 10. The controller 20 may request data according to an automatically set cycle and/or an input command from an external terminal.

Step S220 is a step in which the noise filter 260 performs primary noise filtering on the raw data transmitted from the flow sensor unit 10. The noise filter 260 may be performed using a moving average technique using set bandwidth and time parameters.

Step S230 is the step of calculating the standard index.

For example, the slower the flow rate in the pipe, the higher the noise is generated due to various factors such as the environment within the pipe. Especially when the flow speed is less than 0.3m/sec, it is difficult to distinguish between valid and invalid data due to noise.

Therefore, the present invention applied the Reynolds index to distinguish between flow velocities above and below 0.3 m/sec. Therefore, the controller calculates the Reynolds index after first filtering.

Step S240 is a step to detect whether the Reynolds index value is greater than or equal to the reference value. The present applicant set it to 4000 considering the correlation between flow rate and Reynolds index. Therefore, the controller 20 calculates the Reynolds index value using parameters such as the pipe diameter, flow rate, and temperature, and if the result is 4000 or less, the first filtered data is considered valid data.

Step S250 is a step in which the controller 20 adjusts noise filtering if the Reynolds index value is greater than or equal to the reference value. The noise filter 260 applies a moving average technique to distinguish valid data from raw data within a set bandwidth and time. At this time, the controller 20 adjusts the noise filter 260 by further shortening the upper limit (Ho) and lower limit (Lo) of the bandwidth and the moving average time for secondary noise filtering.

Accordingly, the upper limit of the bandwidth (Ho) of the noise filter 260 is changed to a lower value, and the lower limit of the bandwidth (Ho) is changed to an increased value to be closer to the reference value. Therefore, the bandwidth is reduced compared to first-order filtering.

Additionally, the moving average time of the noise filter 260 is adjusted to be shorter as there is more invalid data in the bandwidth, and longer as there is more valid data in the bandwidth.

That is, the bandwidth and moving average time of the noise filter 260 are adjusted to set values for secondary filtering.

Step S260 is a step in which the controller 20 performs secondary filtering. The noise filter 260 performs secondary filtering by applying the bandwidth and moving average time adjusted in step S250 to extract only valid data from the raw data.

Step S270 is a step in which the controller 20 calculates a flow rate value as secondary filtered data. The controller 20 outputs the calculated flow rate value to a display (not shown) or stores it in the storage device 270. Stored data can be transmitted upon request from an external terminal.

Therefore, the present invention can solve the problem of difficulty in extracting valid data due to a lot of noise, which was pointed out as a conventional problem when measuring the flow rate in a pipe with a flow rate of 0.3 m/sec or less by using the configuration and method described above.

Although the present invention has been described above with limited examples and drawings, the present invention is not limited thereto, and of course, various modifications and variations can be made by those skilled in the art to which the present invention pertains.

Those skilled in the art related to this embodiment will understand that the above-described substrate can be implemented in a modified form without departing from its essential characteristics. Therefore, disclosure methods should be considered from an explanatory rather than a restrictive perspective. The scope of the present invention is indicated in the claims rather than the foregoing description, and all differences within the equivalent scope should be construed as being included in the present invention.

10: Flow sensor unit
20: controller
210: receiving unit
220: Flow measurement module
230: Index calculation module
240: Filter control module
250: Output module
260: noise filter
270: storage device
280: sensor control unit
MC: 1st CPU
SC: 2nd CPU

Claims (8)

A flow sensor unit that measures either the flow rate or the water level within the pipe; and
A controller that calculates the flow rate by filtering the raw data received from the flow sensor unit; Including,
The controller is
When a flow speed of 0.3 m/sec or less is detected, the bandwidth and moving average time of the noise filter are adjusted to go through a noise removal filtering process and then the flow rate value is calculated; A low flow rate flow measurement system featuring.
A flow sensor unit that measures either the flow rate or the water level within the pipe; and
A controller that calculates the flow rate by filtering the raw data received from the flow sensor unit; Including,
The controller is
Calculate the Reynolds index value and, if it falls within a set threshold, adjust the bandwidth and moving average time of the noise filter to go through a noise removal filtering process and then calculate the flow rate value; A low flow rate flow measurement system featuring.
The method of claim 1, wherein the controller
A receiving unit that receives data from the flow sensor unit;
an index calculation module that calculates the Reynolds index using at least one parameter of the diameter of the pipe, temperature, and flow rate;
a filter control module that adjusts the bandwidth and moving average time of the noise filter when the index value calculated by the index calculation module corresponds to a set threshold; and
An output module 250 that calculates a flow rate value as valid data filtered by a noise filter; A low flow rate flow measurement system comprising a.
The method of claim 1 or claim 2, wherein the controller
a storage device that stores data; A low flow rate flow measurement system further comprising:
The method in claim 3, wherein the noise filter is
Second filtering of the raw data according to the Reynolds index value calculated after the first filtering; A low flow rate flow measurement system featuring.
The method of claim 1 or claim 2, wherein the controller
Including a first CPU and a second CPU,
The first CPU includes a flow rate measurement module that receives raw data from the flow sensor unit and measures the flow rate after primary noise filtering; Including,
The second CPU is
an index calculation module that calculates the Reynolds index using at least one parameter of the diameter of the pipe, temperature, and flow rate;
a filter control module that adjusts the bandwidth and moving average time of the noise filter when the index value calculated by the index calculation module corresponds to a set threshold; and
An output module that calculates a flow rate value as valid data filtered by a noise filter; A low flow rate flow measurement system featuring.
Detecting one or more of the water level and flow rate by the flow sensor unit; and
Calculating the flow rate in the controller using data detected by the flow sensor unit; Including,
The flow rate calculation stage of the controller is
Primary noise filtering of raw data;
Calculating a Reynolds index value and detecting whether the calculated index value corresponds to a threshold value;
adjusting the bandwidth and moving average time of the noise filter if the threshold value is met;
Secondary noise filtering to remove noise;
A low-flow rate flow measurement method comprising: calculating a flow rate from data extracted after secondary noise filtering.
The method of claim 7, wherein the threshold is
Reynolds exponent less than 4000; A low flow rate flow measurement method characterized by

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