CN116295675A - Quick response method of low-power consumption electromagnetic water meter, computer equipment and electromagnetic water meter - Google Patents
Quick response method of low-power consumption electromagnetic water meter, computer equipment and electromagnetic water meter Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F1/00—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow
- G01F1/56—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by using electric or magnetic effects
- G01F1/58—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by using electric or magnetic effects by electromagnetic flowmeters
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F1/00—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow
- G01F1/56—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by using electric or magnetic effects
- G01F1/58—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by using electric or magnetic effects by electromagnetic flowmeters
- G01F1/588—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by using electric or magnetic effects by electromagnetic flowmeters combined constructions of electrodes, coils or magnetic circuits, accessories therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
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- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F15/00—Details of, or accessories for, apparatus of groups G01F1/00 - G01F13/00 insofar as such details or appliances are not adapted to particular types of such apparatus
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- G01F15/00—Details of, or accessories for, apparatus of groups G01F1/00 - G01F13/00 insofar as such details or appliances are not adapted to particular types of such apparatus
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- G01F15/065—Indicating or recording devices with transmission devices, e.g. mechanical
- G01F15/066—Indicating or recording devices with transmission devices, e.g. mechanical involving magnetic transmission devices
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- G—PHYSICS
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- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F25/00—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume
- G01F25/10—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume of flowmeters
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
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Abstract
The invention discloses a fast response method of a low-power consumption electromagnetic water meter based on Kalman filtering, which comprises the following steps: acquiring original excitation data, and extracting positive excitation data and negative excitation data from the original excitation data; generating positive excitation effective data according to the positive excitation data, and generating negative excitation effective data according to the negative excitation data; combining the positive excitation effective data and the negative excitation effective data into effective flow data; inputting the effective flow data into a flow array; judging whether the effective flow data of the current period in the flow array is a preset multiple of the effective flow data of the previous period, and if so, filling the flow array and outputting initial flow data after filtering the effective flow data of the current period; and carrying out Kalman filtering processing on the initial flow data to generate target flow data. The invention also discloses computer equipment and an electromagnetic water meter. By adopting the invention, the power consumption can be effectively reduced, and the flow response speed can be improved.
Description
Technical Field
The invention relates to the technical field of water meters, in particular to a quick response method of a low-power-consumption electromagnetic water meter, computer equipment and the electromagnetic water meter.
Background
Kalman filtering (Kalman filtering) is an algorithm that uses a linear system state equation to optimally estimate the state of the system by inputting and outputting observed data through the system. The optimal estimate can also be seen as a filtering process, since the observed data includes the effects of noise and interference in the system.
In data processing, a kalman filter algorithm is often used. The parameters Q and R in the traditional Kalman filter are calculated by a fixed formula, and then the data are continuously processed through iteration. However, the filtering effect of the kalman filtering algorithm is still significant before the data is amplified, but after the data is amplified, the curve after the kalman filtering still has small jitter because the values of the parameter Q and the parameter R are both fixed. Therefore, the existing water meter filtering technology based on Kalman filtering cannot adapt to the requirements of different flow data, and further influences the accuracy of water meter measurement.
In addition, the current electromagnetic water meter powered by a battery generally adopts a constant-current excitation technology, but the problems of low excitation efficiency, long excitation time, larger power consumption and the like are generally existed; therefore, in order to reduce frequent replacement of the battery and save the electric power, it is common to estimate the flow rate at each instant by measuring for several seconds or several tens of seconds in such a way that excitation is performed once (i.e., measurement is performed once) for several seconds or several tens of seconds; however, this results in poor real-time measurement and slow response.
In summary, as the requirement of the water industry on the real-time performance of the measurement data is higher and longer, the requirement on the replacement-free time of the battery is longer, so that the design of not only improving the measurement frequency, but also reducing the power consumption is more and more important for the electromagnetic water meter.
Disclosure of Invention
The invention aims to solve the technical problem of providing a quick response method of a low-power consumption electromagnetic water meter, computer equipment and the electromagnetic water meter, which can effectively reduce power consumption and improve flow response speed.
In order to solve the technical problems, the invention provides a fast response method of a low-power consumption electromagnetic water meter based on Kalman filtering, which comprises the following steps: acquiring original excitation data, and extracting positive excitation data and negative excitation data from the original excitation data; generating positive excitation effective data according to the positive excitation data, and generating negative excitation effective data according to the negative excitation data; combining the positive excitation effective data and the negative excitation effective data into effective flow data; inputting the effective flow data into a flow array; judging whether the effective flow data in the current period in the flow array is a preset multiple of the effective flow data in the previous period, if so, performing filtering processing on the effective flow data in the current period, filling the flow array, outputting initial flow data, and if not, outputting the initial flow data; and carrying out Kalman filtering processing on the initial flow data to generate target flow data.
As an improvement of the above solution, the step of generating positive excitation effective data from the positive excitation data includes: extracting initial effective data from the positive excitation data to perform filtering processing so as to generate reference effective data; judging whether the reference effective data is a first group of data for starting up, if so, filling an effective array according to the reference effective data, and if not, inputting the reference effective data into the effective array; performing cis-position calculation on the reference effective data in the effective array; and extracting target effective data from the effective array and performing filtering processing to generate positive excitation effective data.
As an improvement of the above solution, the step of generating negative excitation valid data according to the negative excitation data includes: extracting initial effective data from the negative excitation data to perform filtering processing so as to generate reference effective data; judging whether the reference effective data is a first group of data for starting up, if so, filling an effective array according to the reference effective data, and if not, inputting the reference effective data into the effective array; performing cis-position calculation on the reference effective data in the effective array; and extracting target effective data from the effective array and performing filtering processing to generate negative excitation effective data.
As an improvement of the scheme, the standard effective data in the effective array corresponding to the positive excitation data is subjected to cis-position calculation according to the formula { BufP [ n ] - (BufN [ n ] +BufN [ n+1 ])/2 }/2; performing cis-position calculation on the reference effective data in the effective array corresponding to the negative excitation data according to a formula { (BufP [ n ] +BufP [ n+1 ])/2-BufN [ n+1] }/2; wherein BufP [ n ] is the reference effective data corresponding to the positive excitation array, and BufN [ n ] is the reference effective data corresponding to the negative excitation array.
As an improvement of the above solution, the step of extracting the target effective data from the effective array and performing filtering processing to generate positive excitation effective data includes: and extracting a preset number of target effective data from the effective array, and carrying out average value processing on the target effective data to generate positive excitation effective data.
As an improvement of the above solution, the step of extracting the target effective data from the effective array and performing filtering processing to generate negative excitation effective data includes: and extracting a preset number of target effective data from the effective array, and carrying out average value processing on the target effective data to generate negative excitation effective data.
As an improvement of the above-described aspect, the step of extracting the initial effective data from the positive excitation data and performing the filtering process to generate the reference effective data includes: and carrying out bubbling sequencing on the positive excitation data, extracting a preset number of initial effective data from the sequenced positive excitation data, and carrying out average processing on the initial effective data to generate reference effective data.
As an improvement of the above-mentioned scheme, the step of extracting the initial effective data from the negative excitation data and performing the filtering process to generate the reference effective data includes: and carrying out bubbling sequencing on the negative excitation data, extracting a preset number of initial effective data from the sequenced negative excitation data, and carrying out average processing on the initial effective data to generate reference effective data.
As an improvement of the scheme, the fast response method of the low-power consumption electromagnetic water meter based on the Kalman filtering further comprises the step of collecting original excitation data by adopting an intermittent excitation mode.
As a modification of the above, the preset multiple is 2 times and/or 0.5 times.
As an improvement of the scheme, when the Kalman filtering is carried out on the initial flow data, the Q value and the R value are dynamically adjusted according to the initial flow data.
Correspondingly, the invention also provides computer equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the quick response method of the low-power consumption electromagnetic water meter based on the Kalman filtering when executing the computer program.
Correspondingly, the invention also provides an electromagnetic water meter which is characterized by comprising a detection circuit and the computer equipment, wherein the detection circuit is used for collecting original excitation data.
The implementation of the invention has the beneficial effects that:
the invention adopts an intermittent excitation mode, and can effectively reduce the power consumption by rectangular wave excitation;
in order to enable the electromagnetic water meter to respond faster, when the effective flow data in the current period is found to be the preset multiple of the effective flow data in the previous period, the effective flow data in the current period is filtered and then is filled in the flow array, so that the response speed of the electromagnetic water meter is faster, and the response speed of the flow is greatly improved.
In addition, the invention introduces a unique cis-position calculation method aiming at the jitter of the data curve, thereby realizing the smooth processing of the positive excitation data and the negative excitation data;
furthermore, the invention can dynamically adjust the Q value and the R value according to different flows during Kalman filtering processing, thereby ensuring the stability of different flows.
Drawings
FIG. 1 is a flow chart of an embodiment of a fast response method of a Kalman filtering-based low power consumption electromagnetic water meter of the present invention;
FIG. 2 is a schematic diagram of the original excitation data in the present invention;
FIG. 3 is a schematic diagram of target flow data in the present invention;
fig. 4 is a schematic diagram of an electrode of the electromagnetic induction module according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings, for the purpose of making the objects, technical solutions and advantages of the present invention more apparent. It is only stated that the terms of orientation such as up, down, left, right, front, back, inner, outer, etc. used in this document or the imminent present invention, are used only with reference to the drawings of the present invention, and are not meant to be limiting in any way.
Referring to fig. 1, fig. 1 shows a flowchart of an embodiment of a fast response method of a low power consumption electromagnetic water meter based on kalman filtering according to the present invention, which includes:
s101, acquiring original excitation data, and extracting positive excitation data and negative excitation data from the original excitation data;
the invention adopts an intermittent excitation mode to collect the original excitation data (see figure 2), wherein the original excitation data comprises 16 positive excitation data and 16 negative excitation data, and the data is processed in parallel by using a plurality of tasks, so that the loss of the data is prevented.
S102, generating positive excitation effective data according to the positive excitation data, and generating negative excitation effective data according to the negative excitation data;
specifically, the step of generating positive excitation valid data from the positive excitation data includes:
(1) Extracting initial effective data from the positive excitation data to perform filtering processing so as to generate reference effective data;
during filtering, firstly performing bubbling sequencing on the positive excitation data, extracting a preset number of initial effective data from the sequenced positive excitation data, and performing average value processing on the initial effective data to generate reference effective data;
for example, the normal excitation data is subjected to bubbling sequencing, and the middle 8 initial effective data are taken for average processing, so that the reference effective data can be generated.
(2) Judging whether the reference effective data is the first group of data of the starting-up, if so, filling the effective array according to the reference effective data, and if not, inputting the reference effective data into the effective array;
the effective array includes 12 data. And if the reference effective data is judged to be the first group of data for starting up, the 12 data in the effective array are rapidly filled with the reference effective data.
(3) Performing cis-position calculation on the reference effective data in the effective array;
to prevent jitter of the data curve, a cis-position calculation may be performed on the reference valid data in the valid array. Specifically, the normal calculation is performed on the reference effective data in the effective array corresponding to the positive excitation data according to the formula { BufP [ n ] - (BufN [ n ] +BufN [ n+1 ])/2 }/2, wherein BufP [ n ] is the reference effective data corresponding to the positive excitation array, bufN [ n ] is the reference effective data corresponding to the negative excitation array, and n is an integer.
For example:
{BufP[0]-(BufN[0]+BufN[1])/2}/2，{BufP[1]-(BufN[1]+BufN[2])/2}/2……
(4) And extracting target effective data from the effective array and performing filtering processing to generate positive excitation effective data.
Specifically, a preset number of target effective data can be extracted from the effective array, and average value processing is carried out on the target effective data to generate positive excitation effective data;
for example, the middle 8 target effective data are taken from the effective array to be subjected to mean value processing, so that positive excitation effective data can be generated.
Similarly, the step of generating negative excitation effective data according to the negative excitation data comprises the following steps:
(1) Extracting initial effective data from the negative excitation data to perform filtering processing so as to generate reference effective data;
during filtering, firstly, bubbling sequencing is carried out on the negative excitation data, a preset number of initial effective data are extracted from the sequenced negative excitation data, and average processing is carried out on the initial effective data to generate reference effective data.
(2) Judging whether the reference effective data is the first group of data of the starting-up, if so, filling the effective array according to the reference effective data, and if not, inputting the reference effective data into the effective array;
the effective array includes 12 data. And if the reference effective data is judged to be the first group of data for starting up, the 12 data in the effective array are rapidly filled with the reference effective data.
(3) Performing cis-position calculation on the reference effective data in the effective array;
to prevent jitter of the data curve, a cis-position calculation may be performed on the reference valid data in the valid array. Specifically, the standard effective data in the effective array corresponding to the negative excitation data is subjected to orthotopic calculation according to the formula { (BufP [ n ] +BufP [ n+1 ])/2-BufN [ n+1] }/2, wherein BufP [ n ] is the standard effective data corresponding to the positive excitation array, bufN [ n ] is the standard effective data corresponding to the negative excitation array, and n is an integer.
For example:
{(BufP[0]+BufP[1])/2-BufN[1]}/2，{(BufP[1]+BufP[2])/2-BufN[2]}/2……
(4) And extracting target effective data from the effective array and performing filtering processing to generate negative excitation effective data.
Specifically, a preset number of target effective data can be extracted from the effective array, and average processing is performed on the target effective data to generate negative excitation effective data.
It should be noted that, after 2 periods, 12 data in the two valid arrays can be respectively filled.
S103, combining the positive excitation effective data and the negative excitation effective data into effective flow data;
therefore, the positive excitation effective data and the negative excitation effective data are combined to obtain effective flow data.
S104, inputting the effective flow data into a flow array;
it should be noted that the flow array contains 12 valid flow data.
S105, judging whether the effective flow data of the current period in the flow array is a preset multiple of the effective flow data of the previous period, if so, filtering the effective flow data of the current period, filling the flow array, outputting initial flow data, and if not, outputting the initial flow data;
it should be noted that, because 6 effective flow data are generated in each period, when the flow changes, at least 2 periods are needed to be stabilized, the response speed is slow, and it is difficult to satisfy the application of the on-site electromagnetic water meter; in order to enable the electromagnetic water meter to respond faster, when the effective flow data calculated in the period is found to be the preset multiple of the effective flow data in the previous period, the average value of the 6 effective flow data is filled with 12 effective flow data, so that the response speed of the electromagnetic water meter is faster. Preferably, the preset multiple is 2 times and/or 0.5 times, but not limited thereto, and may be set according to practical situations.
Therefore, by the treatment, the response time from the beginning of water to the stabilization or from the stabilization to 0 can be shortened, and the response speed of the flow rate can be greatly improved.
S106, performing Kalman filtering processing on the initial flow data to generate target flow data.
When the Kalman filtering is performed on the initial flow data, the Q value and the R value are dynamically adjusted according to the initial flow data, so that the stability of different flows is ensured (see FIG. 3).
As shown in fig. 2 and 3, the original excitation data contains a section of data fluctuation, and even if the filtering treatment is performed and the data is stable, certain jitter exists, wherein the previous data jitter is larger; after the quick response method of the low-power consumption electromagnetic water meter based on the Kalman filtering is used for processing, the response speed can be obviously improved, the flow change response is faster, and stable target flow data is finally output through the Kalman filtering.
Correspondingly, the invention also discloses computer equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the quick response method of the low-power consumption electromagnetic water meter based on the Kalman filtering when executing the computer program.
The invention further discloses an electromagnetic water meter, which comprises a detection circuit and computer equipment, wherein the detection circuit is used for collecting original excitation data and sending the original excitation data to the computer equipment for processing. The detection circuit comprises an electromagnetic induction module, a signal acquisition module and an excitation driving module, and specifically:
as shown in fig. 4, the electromagnetic induction module is designed according to faraday electromagnetic induction principle, and generates a magnetic field by applying a varying current to the coil, and induces electromotive forces on the electrodes a and b when water flows through the magnetic field.
The signal acquisition module consists of a low-pass filter and an analog-to-digital converter and is used for extracting signals output by the electromagnetic induction module of the electromagnetic water meter; the analog-to-digital converter adopts a 24-bit ADC, has higher resolution, and can identify weaker output signals so as to accurately measure extremely small flow; meanwhile, the ADC can amplify the low-pass filtered signal by 24 times by utilizing the self gain, so that the advantage of high resolution of the 24-bit ADC is fully exerted, and the interference caused by an external pre-amplifying circuit is avoided.
The excitation driving module consists of an H-bridge circuit, a constant current circuit and a resistance switching circuit and is used for driving an excitation coil in a primary instrument of the electromagnetic water meter; in order to reduce the power consumption, the excitation driving module adopts an intermittent excitation mode, and rectangular wave excitation is input to reduce the power consumption.
Therefore, the invention combines the intermittent excitation mode, kalman filtering and other technologies to form the specific electromagnetic water meter.
The invention is described in further detail below in conjunction with specific experimental data:
the flow data of the water meter of the fast response method of the low-power consumption electromagnetic water meter based on the Kalman filtering are detected by adopting the Siemens water meter and the water meter of the fast response method of the low-power consumption electromagnetic water meter based on the Kalman filtering as a standard meter, and the flow data measured by the Siemens water meter is shown in the following table 1:
TABLE 1
In Table 1, the meter diameter is 50mm (i.e., DN 50); the range ratio is 400 (i.e., R400); q1 is the minimum flow, and the indication value of the water meter is required to meet the minimum flow of the maximum allowable error; q2 is critical flow, which appears between the common flow Q3 and the minimum flow Q1, and divides the flow range into two areas of flow of a high area and a low area with specific maximum allowable error; q3 is the normal flow, namely the maximum flow under the rated working condition, and the water meter is required to work normally and meet the maximum allowable error requirement.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles of the invention, such changes and modifications are also intended to be within the scope of the invention.
Claims (10)
1. The fast response method of the low-power consumption electromagnetic water meter based on the Kalman filtering is characterized by comprising the following steps of:
acquiring original excitation data, and extracting positive excitation data and negative excitation data from the original excitation data;
generating positive excitation effective data according to the positive excitation data, and generating negative excitation effective data according to the negative excitation data;
combining the positive excitation effective data and the negative excitation effective data into effective flow data;
inputting the effective flow data into a flow array;
judging whether the effective flow data in the current period in the flow array is a preset multiple of the effective flow data in the previous period, if so, performing filtering processing on the effective flow data in the current period, filling the flow array, outputting initial flow data, and if not, outputting the initial flow data;
and carrying out Kalman filtering processing on the initial flow data to generate target flow data.
2. The fast response method of a Kalman filtering based low power consumption electromagnetic water meter of claim 1, wherein,
the step of generating positive excitation effective data according to the positive excitation data comprises the following steps: extracting initial effective data from the positive excitation data to perform filtering processing so as to generate reference effective data; judging whether the reference effective data is a first group of data for starting up, if so, filling an effective array according to the reference effective data, and if not, inputting the reference effective data into the effective array; performing cis-position calculation on the reference effective data in the effective array; extracting target effective data from the effective array and performing filtering processing to generate positive excitation effective data;
the step of generating negative excitation effective data according to the negative excitation data comprises the following steps: extracting initial effective data from the negative excitation data to perform filtering processing so as to generate reference effective data; judging whether the reference effective data is a first group of data for starting up, if so, filling an effective array according to the reference effective data, and if not, inputting the reference effective data into the effective array; performing cis-position calculation on the reference effective data in the effective array; and extracting target effective data from the effective array and performing filtering processing to generate negative excitation effective data.
3. The fast response method of a Kalman filtering based low power consumption electromagnetic water meter of claim 2, wherein,
performing cis-position calculation on reference effective data in an effective array corresponding to the positive excitation data according to a formula { BufP [ n ] - (BufN [ n ] +BufN [ n+1 ])/2 }/2;
performing cis-position calculation on the reference effective data in the effective array corresponding to the negative excitation data according to a formula { (BufP [ n ] +BufP [ n+1 ])/2-BufN [ n+1] }/2;
wherein BufP [ n ] is the reference effective data corresponding to the positive excitation array, and BufN [ n ] is the reference effective data corresponding to the negative excitation array.
4. The fast response method of a Kalman filtering based low power consumption electromagnetic water meter of claim 2, wherein,
the step of extracting target effective data from the effective array and performing filtering processing to generate positive excitation effective data comprises the following steps: extracting a preset number of target effective data from the effective array, and carrying out average value processing on the target effective data to generate positive excitation effective data;
the step of extracting target effective data from the effective array and performing filtering processing to generate negative excitation effective data comprises the following steps: and extracting a preset number of target effective data from the effective array, and carrying out average value processing on the target effective data to generate negative excitation effective data.
5. The fast response method of a Kalman filtering based low power consumption electromagnetic water meter of claim 1, wherein,
the step of extracting initial effective data from the positive excitation data and performing filtering processing to generate reference effective data comprises the following steps: performing bubbling sequencing on the positive excitation data, extracting a preset number of initial effective data from the sequenced positive excitation data, and performing average value processing on the initial effective data to generate reference effective data;
the step of extracting initial effective data from the negative excitation data to perform filtering processing to generate reference effective data comprises the following steps: and carrying out bubbling sequencing on the negative excitation data, extracting a preset number of initial effective data from the sequenced negative excitation data, and carrying out average processing on the initial effective data to generate reference effective data.
6. The fast response method of the Kalman filtering-based low-power consumption electromagnetic water meter of claim 1, further comprising the step of acquiring original excitation data by adopting an intermittent excitation mode.
7. The fast response method of a low power consumption electromagnetic water meter based on Kalman filtering according to claim 1, wherein the preset multiple is 2 times and/or 0.5 times.
8. The fast response method of a low power consumption electromagnetic water meter based on Kalman filtering as claimed in claim 1, wherein the Q value and the R value are dynamically adjusted according to the initial flow data when the Kalman filtering is performed on the initial flow data.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 8 when the computer program is executed.
10. An electromagnetic water meter comprising a detection circuit and the computer device of claim 9, wherein the detection circuit is used for collecting raw excitation data.
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