JPH05273010A - Controlling device for fluidic meter - Google Patents

Abstract

PURPOSE:To obtain a controlling device for a fluidic meter which executes highly-precise computation of a flow rate. CONSTITUTION:A flow rate detecting means 20 an output signal of which is used for determining a flow rate is determined. Then, it is decided which of a first fuzzy function storage means 22 and a second fuzzy function storage means 23 should be selected by switching. Moreover, fuzzy inference is executed by using a detection signal and a membership function, a coefficient is determined by approximating a coefficient function of a nonlinear characteristic and an instantaneous flow rate or an integrated flow rate is determined.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a fluidic meter for measuring the flow rate of a fluid such as city gas or LPG gas, and more particularly to a control device having a highly accurate calculation function.

[0002]

2. Description of the Related Art Conventionally, this type of fluidic meter control device is disclosed in, for example, Japanese Patent Application Laid-Open Nos. 1-308921 and 3-95420.
The configuration was as shown in FIGS. 4 and 5.

In the conventional fluidic meter control device of FIG. 4, 1 is a fluidic meter, 2 is a gas pipe, and 3 is a fluidic oscillation element, which causes fluid oscillation by utilizing the kinetic energy of the fluid. A polymer piezoelectric film sensor 4 detects the frequency of fluid oscillation. 5
Is a flow sensor, which is composed of, for example, a heat ray sensor, and measures the flow rate in a small flow rate range. A shutoff valve 6 shuts off the gas supply when an abnormal use state is detected. Reference numeral 7 is a control device, an example of which is shown in FIG.

In FIG. 5, reference numeral 8 is a vibration detecting means, which comprises a polymer piezoelectric film sensor 4, an analog amplifier 9 and a waveform shaping circuit 10. The analog amplifier 9 amplifies the flow rate signal detected by the polymer piezoelectric film sensor 4. Wave shaping circuit 1
0 converts the amplified signal into a pulse signal. Reference numeral 11 is a flow velocity detecting means (for example, a heat ray type flow velocity sensor), which comprises a flow sensor 5 and an A / D converter 12. A signal determination circuit 13 determines which output signal of the vibration detection means 8 or the flow velocity detection means 11 is used to obtain the flow rate based on the value of the oscillation frequency detected by the vibration detection data 8. To do. A counter 14 counts the number of pulses detected by the flow velocity detecting means 11. Reference numeral 15 is a clock control circuit, which supplies it to the A / D converter 12 to operate the flow velocity detecting means 11. A power source 16 supplies power to the entire control device. Reference numeral 17 denotes a power supply control circuit, which controls the power supply supplied to the flow velocity detecting means 11 on-off. Reference numeral 18 denotes a microcomputer, which includes a calculation display control unit 18a, a safety function unit 18b,
The communication function unit 18c. A display unit 19 displays an integrated value obtained by integrating the flow rates by the microcomputer 18.

Next, the operation of the above configuration will be described. When some kind of gas instrument is used, the gas enters the fluidic oscillation element 3 to cause fluid oscillation, and the polymer piezoelectric film sensor 4 of the vibration detection means 8 detects the flow rate change as an AC signal. The AC signal is amplified by the analog amplifier 9 and converted into a pulse signal by the waveform shaping circuit 10. The pulse signal enters the signal determination circuit 13 and determines whether its frequency is higher than a predetermined value. When the value is equal to or larger than the specified value (that is, in the case of a large flow rate range), the signal from the vibration detecting means 8 is sent to the microcomputer 1.
8, and the flow rate is converted by the microcomputer 18,
Further, the integrated flow rate and the like are obtained. When the value is equal to or less than the predetermined value (that is, a small flow rate range), the signal determination unit 13 does not output the signal of the vibration detection unit 8 to the microcomputer 18, but outputs the output signal of the flow sensor 5 to the microcomputer 18,
The flow rate is converted based on the signal and the integrated value is obtained. That is, the flow velocity signal detected by the flow sensor 5 is converted into a pulse signal by the A / D conversion circuit 12. The A / D conversion circuit 12 outputs the number of pulses according to the flow velocity. The number of output pulses is counted by the counter 14 and output to the microcomputer 18. The flow rate is calculated based on this signal.

The clock control circuit 15 is the A / D conversion circuit 1
2 is supplied as a clock pulse for operating the 2. Further, the flow velocity detecting means 11 is used for the power supply control circuit 17 during measurement.
The power source 16 is controlled by. First, a control signal from the microcomputer 18 is input to the power supply control circuit 17, and the power supply control circuit 17 turns off the flow velocity detection means 11 for 5 seconds and turns on for 40 msec.

Next, the vibration detecting means 8 and the flow velocity detecting means 1
The measurement range of No. 1 will be described with reference to FIG. As shown in FIG. 6, when the flow rate Q increases and reaches Q1 (L / H) or more, the microcomputer based on the signal from the vibration detecting means 8 (detects the oscillation frequency of the fluid generated in the fluidic oscillation element 3). The flow rate is calculated at 18. Below that, the flow rate is obtained from the signal of the flow velocity detecting means 11. On the contrary, if the flow rate decreases, Q
When it becomes lower than 0 (L / H), the flow rate is obtained based on the signal of the flow velocity detecting means 11. Next, a method of converting the frequency of the pulse signal output from the vibration detecting means 8 into a flow rate and a method of converting the flow rate from the number of pulses output from the flow velocity detecting means 11 will be described with reference to FIGS. 7 and 8.

The relationship between the flow rate and the oscillation frequency is generally Q = a
・ It is given by F + b. This is changed to the equation K = Q / F = a + b · T for obtaining the flow rate per pulse. Here, K is called a pulse constant and indicates a flow rate value per pulse. a,
b shows a coefficient. The relationship between the pulse constant and the flow rate or the vibration frequency is approximated by a plurality of broken lines due to the non-linear characteristic as shown in FIG. When the cycle of the flow rate pulse exceeds the boundary of the polygonal line approximation, the coefficient is changed to calculate the pulse constant. Therefore, the coefficient is set for each broken line segment. Further, when a very small time t has elapsed without performing the multiplication of b · T, the unit amount α is added to obtain (where α is α = b
・ There is a relation of t, and if α is added until the time of pulse period T is reached, it becomes b · T).

On the other hand, the number of pulses output from the flow velocity detecting means 11 is output from the A / D converter 12 in proportion to the flow rate. Therefore, the flow rate can be obtained from the number of pulses and the coefficient indicating the relationship between the flow rate and the number of pulses.

[0010]

However, in the above-mentioned conventional configuration, since the pulse constant indicating the relationship between the flow rate and the vibration frequency (or period) is linearly approximated, the error becomes large especially near the boundary of the polygonal line and the flow rate is reduced. There was a problem that it could not be measured accurately and that it also had a large effect on the integrated flow rate value. Furthermore, the number of pulses output from the flow velocity detecting means for detecting the flow rate in the small flow rate region is not proportional to the flow rate but has a non-linear relationship, and if proportionally converted, there is a problem that the error becomes extremely large.

The present invention is intended to solve the above problems, and an object of the present invention is to provide a fluidic meter capable of accurately measuring a flow rate.

[0012]

In order to achieve the above object, the present invention comprises a plurality of flow rate detecting means for detecting a fluid flow rate,
A first fuzzy storing a determining means for determining which of the flow rate detecting means detects the flow rate; and a fuzzy function approximating a coefficient function indicating a non-linear characteristic of the fluid flow rate and the output signal of the flow rate detecting means. By a function storage means, a second fuzzy function storage means for storing a fuzzy function approximating a coefficient function indicating a non-linear characteristic of the fluid flow rate and an output signal of another flow rate detection means, and an output signal of the determination means. Switching means for switching to the first fuzzy function storage means or the second fuzzy function storage means, fuzzy inference means for obtaining a coefficient from the output signals of the switching means and the determination means, the inference result and the determination Flow rate calculating means for obtaining a flow rate value from the output signal of the means.

[0013]

According to the present invention, the fluid flow rate in the large flow rate range is detected by any of a plurality of flow rate detecting means, and the detected flow rate signal and the membership function stored in the first fuzzy function storing means are used. Fuzzy inference is performed to find a coefficient indicating the relationship between the flow rate and the oscillation frequency, and then the instantaneous flow rate is calculated from the found coefficient and the detection signal to further find the integrated flow rate. Next, when the fluid flow rate is in the small flow rate region, fuzzy inference is performed from the signal detected by another flow rate detection means and the membership function stored in the second fuzzy function storage means to obtain a coefficient, and the obtained coefficient and pulse number Calculate the flow rate from

In order to obtain the flow rate in the small flow rate range or the large flow rate range in this way, a first membership function is stored which approximates a coefficient function indicating a non-linear relationship between the fluid flow rate and the output signal of a certain flow rate detecting means. Since the fuzzy function storage means or the second fuzzy function storage means for storing the membership function that approximates the coefficient function indicating the nonlinear relationship between the flow rate and another flow rate detection means is obtained by switching, the error of the fluid flow rate is extremely small. Moreover, it can be achieved with high accuracy. As a result, for example, the integrated value, which is the amount of gas used, can be accurately measured.

[0015]

Embodiments of the present invention will now be described with reference to FIGS. 1, 2 and 3
Will be described. In addition, in FIG. 1, FIG.
The same constituent elements as those of are denoted by the same reference numerals.

FIG. 1 is a control block diagram of the fluidic meter controller of the present invention. In FIG. 1, reference numeral 20 denotes a flow rate detection means, for example, a fluidic oscillation element 3 and a vibration detection means 8 for detecting the oscillation frequency (for example, a piezoelectric sensor, a thermistor or the like is used to detect pressure-voltage change or heat-resistance change). ) And a flow velocity detecting means 11 for detecting the flow velocity (for example, a hot wire type sensor or the like outputs the number of pulses corresponding to the flow amount). Here, the fluidic oscillation element 3 and the vibration detecting means 8 detect the fluid flow rate in the large flow rate range. On the other hand, the flow velocity detecting means 11 is attached to the oscillating element 3 for fluidics and measures the flow rate in a small flow rate range. Reference numeral 21 denotes a determination means, which determines which flow rate detection means 20 should detect the flow rate. For example, the output signal of the vibration detection means 8 which detects the oscillation frequency of the fluidic oscillation element 3 is used to determine which of the output signal of the vibration detection means 8 or the flow velocity detection means 11 is to be used to obtain the flow rate, and then output.

Reference numeral 22 denotes a first fuzzy function storage means, which stores a membership function approximating a non-linear relationship between an output signal of a certain flow rate detection means 20 and the flow rate. 23 is the second
The fuzzy function storing means stores the membership function approximating the non-linear relationship between the detection signal of another flow rate detecting means 20 and the flow rate. In this case, as an example, the first fuzzy function storage unit 22 stores a membership function that is a nonlinear approximation of a coefficient function indicating the relationship between the fluid flow rate flowing through the fluidic oscillator 3 and the oscillation frequency. On the other hand, the second fuzzy function storage means 23 stores a membership function that nonlinearly approximates a coefficient function indicating the relationship between the fluid flow rate and the pulse number output from the flow velocity detection means 11. Two
Reference numeral 4 is a switching means, which is set to the first by the output signal of the judging means 21.
The fuzzy function storing means 22 or the second fuzzy function storing means 23 is switched to. Reference numeral 25 is a fuzzy inference means, which performs fuzzy inference from the detected output signal of the flow rate detection means 20 and the membership functions stored in the first or second fuzzy function storage means 22 and 23 to obtain a coefficient. Reference numeral 25 is a flow rate calculation means, which calculates and obtains the flow rate at that time from the detected output signal of the flow rate detection means 20 and the determined coefficient. Reference numeral 27 is a flow rate integrating means, which integrates the obtained flow rates to obtain an integrated value.

Next, the operation of the above configuration will be described. When the gas starts to be used, the flow rate detecting means 20 detects and outputs the flow rate signal. The determining means 20 determines which flow rate detecting means 20 based on the signal value detected by the flow rate detecting means 20 in order to obtain the flow rate.
Determine whether to perform the calculation with the signal of. When determined, it is output to the switching means 24.

The switching means 24 determines whether to switch to the first fuzzy function storage means 22 or the second fuzzy function storage means 23 based on the signal. Judgment means 2
Flow rate detecting means 20 having 1 (for example, vibration detecting means 8 or the like)
Is selected, the first fuzzy function storage means 21 is switched to. When the determination unit 20 selects another flow rate detection unit 20 (for example, the flow velocity detection unit 11 or the like), the switching unit 24 is set to the second
The fuzzy function storage means 23 is switched to.

The signal detected by the flow rate detecting means 20 and the flow rate have a non-linear relationship, and the coefficient at that time (a coefficient given by the ratio of the flow rate and the output signal of the flow rate detecting means) and the output signal of the flow rate detecting means 20. The relationship with is a non-linear function as shown in FIG. Therefore, in the first and second fuzzy function storage means 22 and 23, the nonlinear characteristic of the coefficient is nonlinearly approximated by the membership function. Here, the membership function of the first fuzzy function storage means 22 indicates, for example, a function in a region where the detection signal is larger than F2. Further, the membership function of the second fuzzy function storage means 23 indicates, for example, a function in a region where the detection signal is smaller than F1. Next, the contents of the nonlinear approximation by the membership function will be described in the case of frequency and coefficient.

As the membership function L (F), for example, a function as shown in FIG. 3 is used. The horizontal axis indicates the flow rate detecting means 20.
Is the detection signal, and the vertical axis is the grade (maximum 1.0).
The relationship between the flow rate and the detection signal of the flow rate detecting means 20 is measured in advance, and then the relationship between the coefficient and the detecting means of the flow rate detecting means 20 as shown in FIG. 2 is obtained. Next, the area of the detection signal of the flow rate detecting means 20 corresponding to the flow rate range to be measured is divided. The division point corresponds to the peak point of the membership function, and the range of the divided detection signal corresponds to half the spread of the bottom of the membership function L (F). It is assumed that the detection signal area is divided into n points. The boundary detection signals are F ₁ , F ₂ , ..., F _n, and the coefficient values at that time are g (F ₁ ), g (F ₂ ), ..., G (F _n ) .L
It is given by n (F).

Therefore, the non-linear coefficient function shown in FIG. 2 (broken line) is approximated by the fuzzy reasoning from the membership functions sharing the region of the detection signal. Next, the content of inference will be described.

Fuzzy inference is performed from the signal detected by the flow rate detecting means 20 and the above-mentioned membership function. The fuzzy inference means 25 comprises a fitness calculation means 25a and an addition means 25b. The fitness calculating means 25a substitutes the detected signal into the membership function to obtain the fitness. The calculated matching degree is added by the adding means 25b to obtain a coefficient δ corresponding to the frequency.

That is, the coefficient function is the following equation δ (F) = Σg
It is given by (F _i ) · L _i (F). On the other hand, when an output signal from another flow rate detection means 20 enters the determination means 21,
The switching means 24 switches from the first fuzzy function storage means to the second fuzzy function storage means or from the second fuzzy function storage means to fuzzy inference to obtain coefficients.

Next, the instantaneous flow rate Q is calculated by the flow rate calculation means 26 from the calculated coefficient δ and the detection signal F by the formula Q = δ · F. The integrated flow rate calculation means 27 adds the instantaneous flow rate Q to obtain the total used flow rate. The display means 19 displays the calculated integrated value.

According to the configuration of this embodiment, the coefficient indicating the relationship between the flow rate and the output signal of the flow rate detecting means 20 is switched using a fuzzy function (membership function) that is nonlinearly approximated over the entire flow rate range to be measured. By doing so, it is possible to approximate the inherent non-linear characteristics, so that it is possible to perform highly accurate flow rate calculation, and as a result, it is possible to accurately measure flow rate such as integrated flow rate.

[0027]

As described above, the fluidic meter control device of the present invention has a plurality of flow rate detecting means for detecting the fluid flow rate, and a determining means for determining which flow rate detecting means should detect the fluid flow rate. A first fuzzy function storing means for storing a fuzzy function approximating a coefficient function indicating a non-linear characteristic of the fluid flow rate and the output signal of the flow rate detecting means, and a non-linear characteristic of the fluid flow rate and an output signal of the other flow rate detecting means. Switching means for switching the coefficient function indicating the value to the approximated fuzzy function storage means or second fuzzy function storage means,
It consists of fuzzy inference means for obtaining a coefficient from the output signals of the switching means and the judging means, and a flow rate calculating means for obtaining a flow rate value from the inference result and the output signal of the judging means. For example, when the gas starts to be used, the flow rate is first obtained. It is determined which output signal of the flow rate detecting means is to be used, and based on the determination signal, it is determined whether to switch to the first fuzzy function storing means or the second fuzzy function storing means. Of the fuzzy function storage means or the membership function of the second fuzzy function storage means is switched to perform fuzzy inference to obtain a coefficient by approximating a coefficient function having a non-linear characteristic. Since the instantaneous flow rate and integrated flow rate are calculated from the coefficient, the error can be made extremely small compared to the case of linear approximation, and the flow rate can be reduced. Operation there is an effect that can be accurately flow measurement, such as integrated flow since performed to the high system.

[Brief description of drawings]

FIG. 1 is a block diagram of a fluidic meter control device according to an embodiment of the present invention.

FIG. 2 is a membership function diagram approximating a coefficient function stored in the device.

FIG. 3 is a membership function diagram stored in the device.

[Fig. 4] System diagram of a conventional fluidic meter controller

FIG. 5 is a circuit block diagram of the device.

FIG. 6 is a characteristic diagram of a sensor use range in the device.

FIG. 7 is a characteristic diagram of the device.

FIG. 8 is a detailed view of the device.

[Explanation of symbols]

 20 flow rate detection means 21 determination means 22 first fuzzy function storage means 23 first fuzzy function storage means 24 switching means 25 fuzzy inference means 26 flow rate calculation means

Claims (1)

[Claims] 1. A plurality of flow rate detecting means for detecting a fluid flow rate, a determining means for determining which of the flow rate detecting means detects the fluid flow rate, and an output signal of the fluid flow rate and the flow rate detecting means. A first fuzzy function storing means for storing a fuzzy function approximating a coefficient function showing a non-linear characteristic, and a fuzzy function approximating a coefficient function showing a non-linear characteristic of the fluid flow rate and an output signal of another flow rate detecting means A second fuzzy function storing means for storing, a switching means for switching to the first fuzzy function storing means or the second fuzzy function storing means according to an output signal of the judging means, and the switching means and the judging means. A fuzzy inference means for obtaining a coefficient from an output signal and a flow rate calculating means for obtaining a flow rate value from the inference result and the output signal of the judging means. Ikkumeta control device.