Meter reading method and system of intelligent ultrasonic water meter and medium

Abstract

The invention belongs to the technical field of water meter reading, and discloses a meter reading method and system of an intelligent ultrasonic water meter and a medium, and the method comprises the following steps: obtaining a first flow velocity data sequence and a pressure category data sequence of a water pipe and amplitude data of the water pipe in a first time interval; according to the water flow velocity data at the moment corresponding to each pressure category and the amplitude of the fluctuation, obtaining a fitting fluctuation curve segment of each pressure category in the second time interval; the fitting fluctuation curve segments corresponding to all the pressure categories are fused, and a sediment increase and decrease change curve is obtained; filtering the first flow velocity data sequence in combination with the obtained pressure data sequence of the water pipe in the first time interval; and transmitting the obtained filtering flow velocity data sequence to a target server to complete meter reading of the intelligent ultrasonic water meter. By analyzing the increase and decrease change of the sediment in the water pipe, the accuracy of the filtering noise data is improved, and the meter reading accuracy of the intelligent ultrasonic water meter is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of water meter reading, and in particular to a meter reading method, system and medium of an intelligent ultrasonic water meter. Background Art

[0002] Smart ultrasonic water meters calculate water flow velocity by measuring the propagation time difference of ultrasonic waves in water, and then deduce the water flow rate; they can also be connected to remote meter reading systems to transmit water meter readings to a central server via the Internet or communication network. This technology can achieve real-time monitoring and meter reading, reducing the need for manual inspections, and is widely used in various scenarios, such as farmland irrigation, urban water supply, rural water supply, etc.

[0003] During the farmland irrigation process, when the intelligent ultrasonic water meter collects flow rate data, it will be affected by the mechanical vibration of large-scale machinery and equipment in the farmland and the vibration of the water pump operation, which may interfere with the ultrasonic signal and cause abnormal fluctuations in the water flow rate data, that is, there is noise data interference. At the same time, the increase or decrease of sediment in the water pipe will also cause normal fluctuations in the flow rate data (at this time, the fluctuation of the flow rate data is a normal fluctuation). If the flow rate data is directly filtered, it is easy to filter out the flow rate data that causes normal fluctuations due to the increase or decrease of sediment, which reduces the accuracy of the collected data, making the transmitted water meter readings unreliable. Summary of the invention

[0004] In order to overcome the problem that the above-mentioned prior art directly filters the water flow rate data, which easily filters out the actual water flow rate data and reduces the accuracy of the collected data, the present invention provides a meter reading method, system and medium for an intelligent ultrasonic water meter.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: A method for reading a water meter using an intelligent ultrasonic water meter, the method comprising the following steps: Acquire a first flow rate data sequence of a water pipe at a certain opening degree of a water pipe outlet valve collected by the intelligent ultrasonic water meter in a first time interval, and acquire a pressure category data sequence of the water pipe in the first time interval, and amplitude data of the water pipe; According to the water flow rate data and the fluctuation amplitude of each pressure category at the corresponding moment in the pressure category data sequence, a fitting fluctuation curve segment of each pressure category in the second time interval is obtained; The fitting fluctuation curve segments corresponding to all pressure categories are merged to obtain the sediment increase and decrease curve in the first time interval; Combined with the pressure data sequence of the water pipe obtained in the first time interval and the obtained sediment increase and decrease curve, the first flow velocity data sequence is filtered; The filtered flow rate data sequence obtained by filtering is transmitted to the target server, thereby completing the meter reading of the intelligent ultrasonic water meter.

[0006] Preferably, obtaining the pressure category data sequence of the water pipe in the first time interval includes: Obtaining a pressure data sequence of the water pipe in a first time interval; The pressure data with the same pressure value are divided into one category to obtain the pressure category data sequence of the water pipe.

[0007] Preferably, obtaining the amplitude data of the water pipe in the first time interval includes: Acquire a vibration data sequence of the water pipe in a first time interval; According to the peaks and valleys in the vibration data sequence, a number of fluctuations in the vibration data sequence are divided; The difference between the maximum value and the minimum value in each fluctuation is taken as the amplitude of each fluctuation; Thus, the amplitude data of the water pipe can be obtained.

[0008] Preferably, obtaining a fitting fluctuation curve segment of each pressure category in the second time interval according to the water flow rate data and the fluctuation amplitude of each pressure category in the pressure category data sequence at a corresponding moment includes: In chronological order, the water flow rate data and the fluctuation amplitude at the time corresponding to all the pressure data in each pressure category are counted to obtain a second flow rate data sequence and a fluctuation amplitude data sequence corresponding to each pressure category data; Counting the modes in the amplitude data sequence, selecting the mode with the smallest amplitude, and calculating the weight corresponding to each water flow velocity data in the second flow velocity data sequence; According to the weight of each water flow rate data in the second flow rate data sequence, the weighted least square method is used to perform fluctuation curve fitting on all data in the second flow rate data sequence to obtain a fitting fluctuation curve segment of each pressure category in the second time interval.

[0009] Preferably, the fitting fluctuation curve segments corresponding to all pressure categories are merged to obtain the sediment increase and decrease curve in the first time interval, including: Calculate the reliability of the fitted fluctuation curve of each pressure category in the second time interval in reflecting the change of sediment increase and decrease; Obtain the second time interval of the fitting fluctuation curve segment corresponding to each pressure category, and use the fitting fluctuation curve segment corresponding to the second time interval at the target time as the target fitting fluctuation curve segment; According to the credibility of the target fitting fluctuation curve segment reflecting the increase and decrease of sediment, the sediment amount at the target time is calculated; The above steps are repeated to obtain the sedimentation amount at each moment in the first time interval, thereby forming a sediment increase and decrease curve.

[0010] Furthermore, the reliability of the fitting fluctuation curve segment of each pressure category in the second time interval in reflecting the change of sediment increase and decrease is calculated, including: Acquire a third flow rate data sequence within a second time interval; According to the data quantity of the third flow velocity data sequence and the second flow velocity data sequence, and the variance of the time difference corresponding to all two adjacent water flow velocity data in the second flow velocity data sequence, the distribution suitability of the second flow velocity data sequence in the second time interval is calculated; The number of data in the amplitude data sequence, the maximum and minimum values ​​in the amplitude data sequence are obtained, and combined with the number of modes and distribution suitability in the amplitude data sequence, the credibility of the fitted fluctuation curve segment corresponding to each pressure category in reflecting the increase and decrease of sediment is calculated.

[0011] Furthermore, according to the credibility of the target fitting fluctuation curve segment in reflecting the change of sediment increase and decrease, the sediment amount at the target time is calculated, including: According to the credibility of a certain target fitting fluctuation curve segment reflecting the change of sediment increase and decrease, the sum of the credibility of all target fitting fluctuation curve segments reflecting the change of sediment increase and decrease is calculated; The sedimentation amount at the target moment is calculated by combining the number of target fitting fluctuation curve segments, the water velocity value corresponding to the target moment on a certain target fitting fluctuation curve segment, the credibility of a certain target fitting fluctuation curve segment reflecting the increase and decrease of sediment, and the sum of the credibility of all target fitting fluctuation curve segments reflecting the increase and decrease of sediment.

[0012] Preferably, the first flow rate data sequence is filtered in combination with the pressure data sequence of the water pipe in the first time interval and the obtained sediment increase and decrease curve, including: Acquire a first flow rate data sequence and a pressure data sequence in a first time interval; Performing EMD decomposition on the first velocity data sequence to obtain multiple IMF components; The reconstruction weight of each IMF component is calculated based on the Pearson correlation coefficient between the pressure data series and each IMF component, and the Pearson correlation coefficient between the sediment increase and decrease curve and each IMF component; The weighted reconstruction of the EMD decomposition is performed according to the reconstruction weight of each IMF component to obtain a filtered flow velocity data sequence of the first flow velocity data sequence.

[0013] A computer system comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the meter reading method of the intelligent ultrasonic water meter is implemented.

[0014] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the meter reading method of the intelligent ultrasonic water meter.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention obtains a fitting fluctuation curve segment of each pressure category in a second time interval based on the water flow rate data at the corresponding moment of each pressure category in the pressure category data sequence and the amplitude of the fluctuation; the fitting fluctuation curve segments corresponding to all pressure categories are merged to obtain a sediment increase and decrease curve of the first time interval, thereby analyzing the increase and decrease changes of sediments in the water pipe, so as to remove noise data caused by vibration during the filtering process and retain the flow rate data fluctuation caused by the increase and decrease changes of sediments, thereby improving the accuracy of the flow rate data after filtering and ensuring the accuracy of meter reading of the intelligent ultrasonic water meter. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flow chart of the steps of a meter reading method of an intelligent ultrasonic water meter.

[0017] Figure 2 It is a schematic block diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The present invention is described in detail below in combination with the drawings and specific implementation methods.

[0019] It should be understood that when used in this specification, the terms "include" and "comprising" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0020] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention, unless the context clearly indicates otherwise, the singular forms of "a", "an" and "the" are intended to include plural forms.

[0021] It should be further understood that the term “and / or” used in the specification of the present invention refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0022] Example 1 During the farmland irrigation process, when the intelligent ultrasonic water meter collects flow rate data, it will be affected by the mechanical vibration of large-scale machinery and equipment in the farmland, the vibration of the water pump operation, etc., which may interfere with the ultrasonic signal and cause abnormal fluctuations in the flow rate data (that is, noise data). At the same time, the increase or decrease of sediment in the water pipe will also cause normal fluctuations in the flow rate data (at this time, the fluctuation of the flow rate data is a normal fluctuation). If the flow rate data is directly filtered, it is easy to filter out the flow rate data that causes normal fluctuations due to the increase or decrease of sediment, which reduces the accuracy of the collected data, making the transmitted water meter readings unreliable.

[0023] In order to distinguish the influence of sediment and vibration in the water pipe on the data collection of the intelligent ultrasonic water meter and ensure the accuracy of the reading transmission of the intelligent ultrasonic water meter, the present invention provides a meter reading method of the intelligent ultrasonic water meter. In this embodiment, the intelligent ultrasonic water meter is an instrument that uses the principle of ultrasonic wave propagation in water to measure the water flow. It usually does not directly collect water flow data, but indirectly calculates the water flow by measuring the propagation speed of ultrasonic wave in water.

[0024] Specifically, a method for reading a water meter using an intelligent ultrasonic water meter, such as Figure 1 As shown, the method comprises the following steps: Acquire a first flow rate data sequence of a water pipe at a certain opening degree of a water pipe outlet valve collected by the intelligent ultrasonic water meter in a first time interval, and acquire a pressure category data sequence of the water pipe in the first time interval, and amplitude data of the water pipe; According to the water flow rate data and the fluctuation amplitude of each pressure category at the corresponding moment in the pressure category data sequence, a fitting fluctuation curve segment of each pressure category in the second time interval is obtained; The fitting fluctuation curve segments corresponding to all pressure categories are merged to obtain the sediment increase and decrease curve in the first time interval; Combined with the pressure data sequence of the water pipe obtained in the first time interval and the obtained sediment increase and decrease curve, the first flow velocity data sequence is filtered; The filtered flow rate data sequence obtained by filtering is transmitted to the target server, thereby completing the meter reading of the intelligent ultrasonic water meter.

[0025] The present invention obtains a fitting fluctuation curve segment of each pressure category in a second time interval based on the water flow rate data at the corresponding moment of each pressure category in the pressure category data sequence and the amplitude of the fluctuation; the fitting fluctuation curve segments corresponding to all pressure categories are merged to obtain a sediment increase and decrease curve of the first time interval, thereby analyzing the increase and decrease changes of sediments in the water pipe, so as to remove noise data caused by vibration during the filtering process and retain the flow rate data fluctuation caused by the increase and decrease changes of sediments, thereby improving the accuracy of the flow rate data after filtering and ensuring the accuracy of meter reading of the intelligent ultrasonic water meter.

[0026] In a specific embodiment, during the farmland irrigation process, a smart ultrasonic water meter is used to obtain a first flow rate data sequence of a water pipe at a certain opening degree of a water pipe outlet valve in a first time interval. At the same time, a vibration sensor and a pressure sensor are used to respectively collect a vibration data sequence and a pressure data sequence of the corresponding water pipe in the first time interval. The frequency of collection is once per second.

[0027] It should be noted that the valve opening degree of the water pipe outlet remains unchanged during the entire process of each irrigation. When the valve opening degree needs to be changed, the first flow rate data sequence, vibration data sequence and pressure data sequence at a certain fixed valve opening degree are collected.

[0028] This is because the degree of opening of the valve in each water pipe remains unchanged, and the cross-sectional area of ​​the water pipes is the same. If the water pressure is also the same, then according to the basic principles of fluid mechanics, the flow rate should be the same without considering other influencing factors.

[0029] During the continuous irrigation of farmland, the water pressure control system monitors the water pressure in the water pipe according to the set threshold. As water is used for irrigation, the water pressure will gradually decrease to the set lower threshold. At this time, the water pressure control system will activate the corresponding regulation mechanism to increase the water pressure until the water pressure reaches the set upper threshold and the water pressure stops increasing. Due to the continuous irrigation, the water pressure will drop again, and then the water pressure control system will take measures to increase the water pressure to keep the water pressure within the set range. This process is repeated continuously, causing the water pressure in the water pipe to fluctuate.

[0030] In this embodiment, obtaining a pressure category data sequence of a water pipe in a first time interval includes: Obtaining a pressure data sequence of the water pipe in a first time interval; The pressure data with the same pressure value are divided into one category to obtain the pressure category data sequence of the water pipe .

[0031] Take any pipe as an example, at the beginning of irrigation To the current time , in the first time interval [ , ], the pressure data with the same pressure value are divided into one category, and the pressure category data sequence of the pipeline is obtained, which is recorded as .

[0032] In a specific embodiment, obtaining the amplitude data of the water pipe in the first time interval includes: Get the first time interval [ , ]Vibration data sequence R of the inner water pipe; According to the peaks and valleys in the vibration data sequence R, the sequence segments corresponding to the adjacent peak points and valley points are regarded as a fluctuation, and several fluctuations in the vibration data sequence R are divided; The difference between the maximum value and the minimum value in each fluctuation is taken as the amplitude of each fluctuation; Thus, the amplitude data of the water pipe can be obtained.

[0033] In a specific embodiment, according to the water flow rate data and the fluctuation amplitude of each pressure category at the corresponding moment in the pressure category data sequence, a fitting fluctuation curve segment of each pressure category in the second time interval is obtained, including: The water flow rate data and the fluctuation amplitude at the time corresponding to all the pressure data in each pressure category are counted in chronological order to obtain a second flow rate data sequence and an amplitude data sequence corresponding to each pressure category data.

[0034] It is known that the increase of sediment in the water pipe usually leads to a decrease in flow rate at the same pressure. This is because the sediment will occupy part of the space in the water pipe channel, reduce the effective channel area of ​​the water flow, thereby increasing the resistance of the water flow, and the flow rate will also decrease (the basic principle of fluid mechanics). In addition, the sediment in the water pipe may gradually accumulate, or it may decrease with the flushing of the water flow, so the change in the increase or decrease of sediment can be reflected by the change in flow rate under the same water pressure. It is known that the increase of sediment in the water pipe usually leads to a decrease in flow rate at the same pressure. This is because the sediment will occupy part of the space in the water pipe channel, reduce the effective channel area of ​​the water flow, thereby increasing the resistance of the water flow, and the flow rate will also decrease (the basic principle of fluid mechanics). In addition, the sediment in the water pipe may gradually accumulate, or it may decrease with the flushing of the water flow, so the change in the increase or decrease of sediment can be reflected by the change in flow rate under the same water pressure.

[0035] By pressure category For example, in the pressure category At the time when all the pressure data are located, the velocity data and the amplitude data at each moment are counted to obtain the pressure category The corresponding second flow rate data sequence And the volatility data series .

[0036] Count the modes in the amplitude data sequence, select the mode with the smallest amplitude, and calculate the weight corresponding to each water velocity data in the velocity data sequence .

[0037] Due to the influence of external vibration, the ultrasonic signal may be disturbed, resulting in abnormal fluctuations in the flow rate data, that is, noise data. Therefore, the present invention analyzes the flow rate data sequence as much as possible. The flow rate under the same vibration amplitude in the flowmeter can be reduced to reduce the influence of the vibration amplitude change.

[0038] The present invention selects the mode with the smallest amplitude. This is because there may be multiple modes, and selecting the mode with the smallest amplitude can ensure that the vibration effect is small.

[0039] This embodiment also provides a flow rate data sequence The weight of the i-th flow velocity data The calculation formula is: ; in, for The i-th amplitude data in; It is a linear normalization function, which is used to normalize the amplitude data to between 0 and 1; is the absolute value function; Is the majority.

[0040] According to the weight of each water flow rate data in the second flow rate data sequence, the weighted least square method is used to perform fluctuation curve fitting on all data in the second flow rate data sequence to obtain a fitting fluctuation curve segment of each pressure category in the second time interval.

[0041] In this embodiment, the pressure category is obtained. The starting time of all pressure data is , the end time is .

[0042] According to the flow rate data series The weight of each velocity data in is used to calculate the velocity data sequence using the weighted least squares method. All the data in are fitted with fluctuation curves to obtain the velocity data series The corresponding fitting fluctuation curve segment Among them, the horizontal axis of the fitting fluctuation curve segment is time, the vertical axis is flow rate, and the fitting fluctuation curve segment On the horizontal axis, the time interval [ , ]Inside.

[0043] If in the fitting fluctuation curve segment The medium flow rate data increases, which means that the sediment is reduced with the flow erosion; if the fitting fluctuation curve segment The decreasing flow velocity data indicates an increase in sediment accumulation.

[0044] Repeat the above steps to obtain the fitting fluctuation curve segment corresponding to each pressure category data in the pressure category data sequence A, and the second time interval [ , ]Inside.

[0045] In a specific embodiment, the fitting fluctuation curve segments corresponding to all pressure categories are merged to obtain the sediment increase and decrease curve in the first time interval, including: Calculate the credibility of the fitting fluctuation curve segment of each pressure category in the second time interval in reflecting the change of sediment increase and decrease; Obtain the second time interval of the fitting fluctuation curve segment corresponding to each pressure category, and use the fitting fluctuation curve segment corresponding to the second time interval at the target time as the target fitting fluctuation curve segment; According to the credibility of the target fitting fluctuation curve segment reflecting the increase and decrease of sediment, the sediment amount at the target time is calculated; The above steps are repeated to obtain the sedimentation amount at each moment in the first time interval, thereby forming a sediment increase and decrease curve.

[0046] In a specific embodiment, calculating the credibility of the fitting fluctuation curve segment of each pressure category in the second time interval reflecting the change of sediment increase and decrease includes: Acquire a third flow rate data sequence within a second time interval; According to the data quantity of the third flow velocity data sequence and the second flow velocity data sequence, and the variance of the time difference corresponding to all two adjacent water flow velocity data in the second flow velocity data sequence, the distribution suitability of the second flow velocity data sequence in the second time interval is calculated; The number of data in the amplitude data sequence, the maximum and minimum values ​​in the amplitude data sequence are obtained, and combined with the number of modes and distribution suitability in the amplitude data sequence, the credibility of the fitted fluctuation curve segment corresponding to each pressure category in reflecting the increase and decrease of sediment is calculated.

[0047] In this embodiment, the fitting fluctuation curve segment For example, in the time interval [ , ], the velocity data sequence The more data there are, the more evenly distributed they are, and the smaller the vibration interference is, the better the fitting fluctuation curve segment is. Reflected in the time interval [ , ]The more credible the changes in sediment volume are.

[0048] Get time interval[ , ]Flow rate data sequence within , which is the third flow rate data sequence.

[0049] The velocity data series In the time interval [ , The calculation formula of the distribution suitability H within ] is: ; in, is the velocity data series The number of data in is the velocity data series The number of data in is the velocity data series The variance of the time difference between all two adjacent data in .

[0050] Since the flow rate data series The number of velocity data series The greater the proportion of The larger the flow rate data series In the flow rate data series The more uniform the distribution in The smaller the value, the higher the velocity data sequence. In the time interval [ , ] the distribution suitability H should be larger, thus ensuring the fitting fluctuation curve segment The reliability of the fit.

[0051] Then the fitting fluctuation curve segment The reliability of reflecting the changes in sediment increase and decrease The calculation formula is: ; in, is the amplitude data series Mode The number of is the amplitude data series The number of data in , The amplitude data series The maximum and minimum values.

[0052] Due to the majority In the volatility data series The greater the proportion of The smaller the value, the more the same amplitude is and the smaller the amplitude variation is, that is, the smaller the vibration interference is, the better the fitting fluctuation curve segment is. The better the fitting confidence, the better the fitting confidence. Combining the distribution suitability H, we can get the fitting fluctuation curve segment The reliability of reflecting the changes in sediment increase and decrease , The bigger, the more credible.

[0053] Similarly, for the pressure category data series For each pressure category, obtain the fitting fluctuation curve segment corresponding to each pressure category data , and the time interval of the fitting fluctuation curve segment on the horizontal axis .

[0054] In a specific embodiment, according to the credibility of the target fitting fluctuation curve segment reflecting the change of sediment increase and decrease, the sediment amount at the target time is calculated, including: According to the credibility of a certain target fitting fluctuation curve segment reflecting the change of sediment increase and decrease, the sum of the credibility of all target fitting fluctuation curve segments reflecting the change of sediment increase and decrease is calculated; The sedimentation amount at the target moment is calculated by combining the number of target fitting fluctuation curve segments, the water velocity value corresponding to the target moment on a certain target fitting fluctuation curve segment, the credibility of a certain target fitting fluctuation curve segment reflecting the increase and decrease of sediment, and the sum of the credibility of all target fitting fluctuation curve segments reflecting the increase and decrease of sediment.

[0055] In this embodiment, in the time interval [ , ], pressure category data series Each pressure category in is in the second time interval, recorded as .by As an example of the target time, In, get the existence The fitting fluctuation curve segment corresponding to the time interval is used as the target fitting fluctuation curve segment.

[0056] This embodiment provides Deposition amount at time The calculation formula is: ; in, is the number of target fitting fluctuation curve segments, Fit a fluctuation curve segment for the nth target Target time The corresponding flow rate value is The reliability of the fluctuation curve segment fitting for the nth target reflects the change of sediment increase and decrease. The sum of the credibility of all target fitting fluctuation curve segments reflecting the increase and decrease of sediments, It is a linear normalization function used to normalize data values ​​to between 0 and 1.

[0057] because The larger the value is, the more credible the nth target fitting fluctuation curve segment is, and the greater the weight is given. It is known that under the same pressure, a small flow rate indicates more sediments; a large flow rate indicates less sediments. Therefore, The inverse proportional value of represents the amount of deposition.

[0058] Similarly, we get the time interval [ , The amount of sedimentation at each moment between ] constitutes the sediment increase and decrease curve .

[0059] In a specific embodiment, the first flow rate data sequence is filtered in combination with the pressure data sequence of the water pipe in the first time interval and the obtained sediment increase and decrease curve, including: Acquire a first flow rate data sequence and a pressure data sequence in a first time interval; Performing EMD decomposition on the first velocity data sequence to obtain multiple IMF components; The reconstruction weight of each IMF component is calculated based on the Pearson correlation coefficient between the pressure data series and each IMF component, and the Pearson correlation coefficient between the sediment increase and decrease curve and each IMF component; The weighted reconstruction of the EMD decomposition is performed according to the reconstruction weight of each IMF component to obtain a filtered flow velocity data sequence of the first flow velocity data sequence.

[0060] In this embodiment, the time interval [ , ]’s first flow rate data sequence B, and pressure data sequence Z.

[0061] The present invention uses an EMD decomposition algorithm to filter the first flow rate data sequence B. The EMD decomposition algorithm is a well-known technology and will not be described in detail here. The EMD decomposition algorithm can separate the noise component and the useful signal component in the signal.

[0062] Therefore, the present invention assigns greater weights to important signal components during the EMD signal reconstruction process to ensure that the accuracy of the flow rate data change trend and the actual fluctuations in the flow rate data caused by the increase or decrease of sediment in the water pipe are not filtered out during the flow rate data filtering and denoising process.

[0063] In this embodiment, multiple IMF components are obtained by performing EMD decomposition on the first flow velocity data sequence B; generally, a residual component is also obtained.

[0064] Under ideal conditions, according to Bernoulli's principle, when a fluid flows in the same water pipe, the pressure is low where the flow rate is fast, and the pressure is high where the flow rate is slow.

[0065] Therefore, the data transformation trend of an IMF component representing flow velocity data that changes with pressure should be negatively correlated with the pressure data transformation trend; the data transformation trend of an IMF component representing flow velocity data that changes with the increase or decrease of sediment should be negatively correlated with the increase or decrease of sediment.

[0066] Then the reconstruction weight of the jth IMF component is The calculation formula is: ; in, is the pressure data series and the jth IMF component The Pearson correlation coefficient, The sediment increase and decrease curve and the jth IMF component The Pearson correlation coefficient.

[0067] Among them, the Pearson correlation coefficient is a well-known technology, which is rounded to between -1 and 1. The closer it is to -1, the more negatively correlated the two data series are. or The larger it is, the more consistent the jth IMF component is with the pressure change or sediment increase or decrease change, that is, the more important it is and the larger the reconstruction weight is required.

[0068] It should be noted that since the Pearson correlation coefficient ranges from -1 to 1, the reconstruction weight The value range of is between 0 and 2. In order to make the cumulative sum of the reconstruction weights of all IMF components equal to 1, this embodiment uses the reconstruction weight Divide by the cumulative sum of the reconstruction weights of all IMF components to reconstruct the weights Normalization is performed. Thus, the reconstruction weight of each IMF component is obtained, and finally, weighted reconstruction of EMD decomposition is performed according to the reconstruction weight of each IMF component (this is a well-known operation), and the filtered flow velocity data sequence BL of the first flow velocity data sequence B is obtained.

[0069] In a specific embodiment, the filtered flow rate data sequence obtained by filtering is transmitted to a target server, thereby completing the meter reading of the intelligent ultrasonic water meter.

[0070] In this embodiment, the working principle of the known intelligent ultrasonic water meter is based on the fact that when ultrasonic waves propagate in liquid, the flow of the liquid will cause the propagation time of the downstream and upstream to change. This change is proportional to the flow rate of the liquid. By calculating the difference in propagation time, the speed of the liquid is obtained, and then the flow rate is calculated.

[0071] Specifically, the intelligent ultrasonic water meter calculates the flow velocity by measuring the propagation time difference of the ultrasonic signal in the downstream and upstream directions. Since the ultrasonic signal propagates faster in the downstream direction and slower in the upstream direction, the flow velocity of the fluid can be obtained by measuring the time difference in these two directions. Finally, the flow rate of the fluid is calculated based on the product of the flow velocity and the cross-sectional area of ​​the pipe.

[0072] Therefore, the present invention can obtain the flow data sequence of the water pipe according to the obtained filtered flow velocity data sequence BL, transmit the flow data sequence of the water pipe to the central server, and store it; it can also directly transmit the obtained filtered flow velocity data sequence BL to the central server, and then the central server calculates the flow data sequence of the water pipe and stores it. In this way, the meter reading of the intelligent ultrasonic water meter is accurately completed; it can also transmit the obtained filtered flow velocity data sequence BL to the edge server for calculation, obtain the flow data sequence of the water pipe, and then transmit the flow data sequence of the water pipe to the central server and store it.

[0073] See also Figure 2 , Figure 2 5 is a schematic block diagram of a computer device provided by an embodiment of the present invention. The computer device 500 is a server, which can be an independent server or a server cluster composed of multiple servers.

[0074] See also Figure 2 The computer device 500 includes a processor 502 , a memory and a network interface 505 connected via a system bus 501 , wherein the memory may include a non-volatile storage medium 503 and an internal memory 504 .

[0075] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. When the computer program 5032 is executed, the processor 502 can execute a meter reading method for an intelligent ultrasonic water meter.

[0076] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500 .

[0077] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute the meter reading method of the intelligent ultrasonic water meter.

[0078] The network interface 505 is used for network communication, such as providing data information transmission, etc. Those skilled in the art will understand that Figure 2 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device 500 to which the solution of the present invention is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0079] The processor 502 is used to run the computer program 5032 stored in the memory to implement the meter reading method of the intelligent ultrasonic water meter disclosed in the embodiment of the present invention.

[0080] Those skilled in the art will understand that Figure 2 The embodiments of the computer device shown in the figure do not constitute a limitation on the specific composition of the computer device. In other embodiments, the computer device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. For example, in some embodiments, the computer device may only include a memory and a processor. In such embodiments, the structure and function of the memory and the processor are the same as those of the embodiment of the present invention. Figure 2 The embodiments shown are consistent and will not be described again here.

[0081] It should be understood that in the embodiment of the present invention, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0082] In another embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium may be a non-volatile computer-readable storage medium. The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the meter reading method of the intelligent ultrasonic water meter disclosed in the embodiment of the present invention is implemented.

[0083] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the above-described equipment, devices and units can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. Those of ordinary skill in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0084] In the several embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. Units with the same function may also be combined into one unit. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices or units, or may be an electrical, mechanical or other form of connection.

[0085] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0086] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0087] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), disk or optical disk and other media that can store program codes.

[0088] Obviously, the above embodiments of the present invention are only examples for clearly explaining the present invention, and are not intended to limit the implementation methods of the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for reading a water meter using an intelligent ultrasonic water meter, characterized in that: The method comprises the following steps: Acquire a first flow rate data sequence of a water pipe at a certain opening degree of a water pipe outlet valve collected by the intelligent ultrasonic water meter in a first time interval, and acquire a pressure category data sequence of the water pipe in the first time interval, and amplitude data of the water pipe; According to the water flow rate data and the fluctuation amplitude of each pressure category at the corresponding moment in the pressure category data sequence, a fitting fluctuation curve segment of each pressure category in the second time interval is obtained; The fitting fluctuation curve segments corresponding to all pressure categories are merged to obtain the sediment increase and decrease curve in the first time interval; Combined with the pressure data sequence of the water pipe obtained in the first time interval and the obtained sediment increase and decrease curve, the first flow velocity data sequence is filtered; The filtered flow rate data sequence obtained by filtering is transmitted to the target server, thereby completing the meter reading of the intelligent ultrasonic water meter.

2. The meter reading method of an intelligent ultrasonic water meter according to claim 1, characterized in that: Obtain the pressure category data sequence of the water pipe in the first time interval, including: Obtaining a pressure data sequence of the water pipe in a first time interval; The pressure data with the same pressure value are divided into one category to obtain the pressure category data sequence of the water pipe.

3. The meter reading method of an intelligent ultrasonic water meter according to claim 1, characterized in that: Obtain the amplitude data of the water pipe in the first time interval, including: Acquire a vibration data sequence of the water pipe in a first time interval; According to the peaks and valleys in the vibration data sequence, a number of fluctuations in the vibration data sequence are divided; The difference between the maximum value and the minimum value in each fluctuation is taken as the amplitude of each fluctuation; Thus, the amplitude data of the water pipe can be obtained.

4. The meter reading method of an intelligent ultrasonic water meter according to claim 1, characterized in that: According to the water flow rate data and the fluctuation amplitude of each pressure category at the corresponding moment in the pressure category data sequence, a fitting fluctuation curve segment of each pressure category in the second time interval is obtained, including: In chronological order, the water flow rate data and the fluctuation amplitude at the time corresponding to all the pressure data in each pressure category are counted to obtain a second flow rate data sequence and a fluctuation amplitude data sequence corresponding to each pressure category data; Counting the modes in the amplitude data sequence, selecting the mode with the smallest amplitude, and calculating the weight corresponding to each water flow velocity data in the second flow velocity data sequence; According to the weight of each water flow rate data in the second flow rate data sequence, the weighted least square method is used to perform fluctuation curve fitting on all data in the second flow rate data sequence to obtain a fitting fluctuation curve segment of each pressure category in the second time interval.

5. The meter reading method of an intelligent ultrasonic water meter according to claim 1, characterized in that: The fitting fluctuation curve segments corresponding to all pressure categories are merged to obtain the sediment increase and decrease curve of the first time interval, including: Calculate the reliability of the fitted fluctuation curve of each pressure category in the second time interval in reflecting the change of sediment increase and decrease; Obtain the second time interval of the fitting fluctuation curve segment corresponding to each pressure category, and use the fitting fluctuation curve segment corresponding to the second time interval at the target time as the target fitting fluctuation curve segment; According to the credibility of the target fitting fluctuation curve segment reflecting the increase and decrease of sediment, the sediment amount at the target time is calculated; The above steps are repeated to obtain the sedimentation amount at each moment in the first time interval, thereby forming a sediment increase and decrease curve.

6. The meter reading method of an intelligent ultrasonic water meter according to claim 5, characterized in that: Calculate the credibility of the fitting fluctuation curve segment of each pressure category in the second time interval to reflect the change of sediment increase and decrease, including: Acquire a third flow rate data sequence within a second time interval; According to the data quantity of the third flow velocity data sequence and the second flow velocity data sequence, and the variance of the time difference corresponding to all two adjacent water flow velocity data in the second flow velocity data sequence, the distribution suitability of the second flow velocity data sequence in the second time interval is calculated; The number of data in the amplitude data sequence, the maximum and minimum values ​​in the amplitude data sequence are obtained, and combined with the number of modes and distribution suitability in the amplitude data sequence, the credibility of the fitted fluctuation curve segment corresponding to each pressure category in reflecting the increase and decrease of sediment is calculated.

7. The meter reading method of an intelligent ultrasonic water meter according to claim 5, characterized in that: According to the credibility of the target fitting fluctuation curve segment reflecting the increase and decrease of sediment, the sediment amount at the target time is calculated, including: According to the credibility of a certain target fitting fluctuation curve segment reflecting the change of sediment increase and decrease, the sum of the credibility of all target fitting fluctuation curve segments reflecting the change of sediment increase and decrease is calculated; The sedimentation amount at the target moment is calculated by combining the number of target fitting fluctuation curve segments, the water velocity value corresponding to the target moment on a certain target fitting fluctuation curve segment, the credibility of a certain target fitting fluctuation curve segment reflecting the increase and decrease of sediment, and the sum of the credibility of all target fitting fluctuation curve segments reflecting the increase and decrease of sediment.

8. The meter reading method of an intelligent ultrasonic water meter according to claim 1, characterized in that: Combined with the pressure data sequence of the water pipe in the first time interval and the obtained sediment increase and decrease curve, the first flow velocity data sequence is filtered, including: Acquire a first flow rate data sequence and a pressure data sequence in a first time interval; Performing EMD decomposition on the first velocity data sequence to obtain multiple IMF components; The reconstruction weight of each IMF component is calculated based on the Pearson correlation coefficient between the pressure data series and each IMF component, and the Pearson correlation coefficient between the sediment increase and decrease curve and each IMF component; The weighted reconstruction of the EMD decomposition is performed according to the reconstruction weight of each IMF component to obtain a filtered flow velocity data sequence of the first flow velocity data sequence.

9. A computer system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the meter reading method of the intelligent ultrasonic water meter according to any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the meter reading method of the intelligent ultrasonic water meter according to any one of claims 1 to 8.

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