A Meter Reading Method, System and Medium for an Intelligent Ultrasonic Water Meter

Abstract

The present invention belongs to the technical field of water meter reading, and discloses a method, system and medium for reading an intelligent ultrasonic water meter, as follows: obtaining a first flow velocity data sequence, a pressure category data sequence of a water pipe and the wave amplitude data of the water pipe within a first time interval; obtaining a fitting wave curve segment of each pressure category in a second time interval according to the water flow velocity data and the fluctuating wave amplitude corresponding to each moment of each pressure category; fusing the fitting wave curve segments corresponding to all pressure categories to obtain a sediment increase and decrease change curve; and combining with the pressure data sequence of the water pipe obtained within the first time interval, performing filtering processing on the first flow velocity data sequence; transmitting the obtained filtered flow velocity data sequence to a target server to complete the reading of the intelligent ultrasonic water meter. The present invention improves the accuracy of filtered noise data by analyzing the increase and decrease of sediments in the water pipe, and ensures the accuracy of reading the intelligent ultrasonic water meter.

Description

Technical Field

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

[0002] An intelligent ultrasonic water meter calculates the water flow velocity by measuring the time difference of ultrasonic waves propagating in water, and then calculates the water flow; it can also be connected to a remote meter reading system to transmit the water meter reading to a central server through the Internet or a 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, and rural water supply.

[0003] During the process of farmland irrigation, when an intelligent ultrasonic water meter collects flow velocity data, it will be affected by the mechanical vibration of large-scale mechanical equipment and the vibration of water pump operation in the farmland, which may interfere with the ultrasonic signal and cause abnormal fluctuations in the water flow velocity data, that is, there is interference of noise data. At the same time, the increase and decrease of sediment in the water pipe will also cause normal fluctuations in the flow velocity data (at this time, the fluctuations in the flow velocity data belong to normal fluctuations). If the flow velocity data is directly filtered, it is easy to filter out the flow velocity data caused by the increase and decrease of sediment, reducing the accuracy of the collected data, thus making the transmitted water meter reading untrustworthy. Summary of the Invention

[0004] In order to overcome the problem that directly filtering the water flow velocity data in the above-mentioned prior art is likely to filter out the actual water flow velocity data, resulting in a reduction in the accuracy of the collected data, the present invention provides a method, a system and a medium for reading an intelligent ultrasonic water meter.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A method for reading an intelligent ultrasonic water meter, the method includes the following steps:

[0007] Obtain the first flow velocity data sequence of the water pipe collected by the intelligent ultrasonic water meter within a first time interval at a certain opening degree of the water pipe outlet valve, and obtain the pressure category data sequence of the water pipe and the amplitude data of the water pipe within the first time interval;

[0008] According to the water flow velocity data corresponding to each pressure category at the corresponding moment in the pressure category data sequence and the fluctuating amplitude, obtain the fitting fluctuation curve segment of each pressure category in a second time interval;

[0009] Fuse the fitting fluctuation curve segments corresponding to all pressure categories to obtain the sediment increase and decrease change curve in the first time interval;

[0010] Combined with obtaining the pressure data sequence of the water pipe within the first time interval and the obtained sediment increase and decrease change curve, filter the first flow velocity data sequence;

[0011] Transmit the filtered flow velocity data sequence obtained by the filtering process to the target server, thereby completing the meter reading of the intelligent ultrasonic water meter.

[0012] Preferably, obtain the pressure category data sequence of the water pipe within the first time interval, including:

[0013] Obtain the pressure data sequence of the water pipe within the first time interval;

[0014] Divide the pressure data with the same pressure value into one category to obtain the pressure category data sequence of the water pipe.

[0015] Preferably, obtain the amplitude data of the water pipe within the first time interval, including:

[0016] Obtain the vibration data sequence of the water pipe within the first time interval;

[0017] According to the peaks and valleys in the vibration data sequence, divide several fluctuations in the vibration data sequence;

[0018] Use the difference between the maximum value and the minimum value in each fluctuation as the amplitude of each fluctuation;

[0019] Thus, obtain the amplitude data of the water pipe.

[0020] Preferably, according to the water flow velocity data corresponding to each pressure category at the corresponding moment in the pressure category data sequence and the amplitude of the fluctuation, obtain the fitted fluctuation curve segment of each pressure category in the second time interval, including:

[0021] In chronological order, count the water flow velocity data and the amplitude of the fluctuation corresponding to all pressure data in each pressure category to obtain the second flow velocity data sequence and the amplitude data sequence corresponding to each pressure category data;

[0022] Statistically analyze the mode in the amplitude data sequence, select the mode with the smallest amplitude, and calculate the weight corresponding to each water flow velocity data in the second flow velocity data sequence;

[0023] According to the weight of each water flow velocity data in the second flow velocity data sequence, use the weighted least squares method to perform fluctuation curve fitting on all data in the second flow velocity data sequence to obtain the fitted fluctuation curve segment of each pressure category in the second time interval.

[0024] Preferably, fuse the fitted fluctuation curve segments corresponding to all pressure categories to obtain the sediment increase and decrease change curve in the first time interval, including:

[0025] Calculate the credibility of the fitting fluctuation curve of each pressure category in the second time interval reflecting the increase or decrease of sediment;

[0026] 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 where the target moment is located as the target fitting fluctuation curve segment;

[0027] Calculate the sediment deposition amount at the target moment according to the credibility of the target fitting fluctuation curve segment reflecting the increase or decrease of sediment;

[0028] Repeat the above steps to obtain the sediment deposition amount at each moment in the first time interval, thereby forming a curve of the increase or decrease of sediment.

[0029] Further, calculating the credibility of the fitting fluctuation curve segment of each pressure category in the second time interval reflecting the increase or decrease of sediment includes:

[0030] Obtain the third flow velocity data sequence in the second time interval;

[0031] Calculate the distribution suitability of the second flow velocity data sequence in the 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 adjacent two water flow velocity data in the second flow velocity data sequence;

[0032] Obtain the data quantity in the amplitude data sequence, the maximum value and the minimum value in the amplitude data sequence, and calculate the credibility of the fitting fluctuation curve segment corresponding to each pressure category reflecting the increase or decrease of sediment in combination with the quantity of the mode in the amplitude data sequence and the distribution suitability.

[0033] Further, calculating the sediment deposition amount at the target moment according to the credibility of the target fitting fluctuation curve segment reflecting the increase or decrease of sediment includes:

[0034] Calculate the sum value of the credibility of all target fitting fluctuation curve segments reflecting the increase or decrease of sediment according to the credibility of a certain target fitting fluctuation curve segment reflecting the increase or decrease of sediment;

[0035] Calculate the sediment deposition amount at the target moment in combination with the quantity of the target fitting fluctuation curve segments, the water flow 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 or decrease of sediment, and the sum value of the credibility of all target fitting fluctuation curve segments reflecting the increase or decrease of sediment.

[0036] Preferably, in combination with the pressure data sequence of the water pipe in the first time interval and the obtained curve of the increase or decrease of sediment, perform filtering processing on the first flow velocity data sequence, including:

[0037] Obtain the first flow velocity data sequence and pressure data sequence for the first time interval;

[0038] Perform EMD decomposition on the first flow velocity data sequence to obtain multiple IMF components;

[0039] Calculate the reconstruction weight of each IMF component based on the Pearson correlation coefficient between the pressure data sequence and each IMF component, and the Pearson correlation coefficient between the sediment increase and decrease change curve and each IMF component;

[0040] Perform weighted reconstruction of EMD decomposition according to the reconstruction weight of each IMF component to obtain the filtered flow velocity data sequence of the first flow velocity data sequence.

[0041] A computer system includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the meter reading method of the intelligent ultrasonic water meter described above.

[0042] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the processor executes the meter reading method of the intelligent ultrasonic water meter described above.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] The present invention obtains the fitting fluctuation curve segment of each pressure category in the second time interval according to the water flow velocity data and the fluctuation amplitude corresponding to each pressure category moment in the pressure category data sequence; fuses the fitting fluctuation curve segments corresponding to all pressure categories to obtain the sediment increase and decrease change curve in the first time interval, so as to analyze the sediment increase and decrease change in the water pipe, and remove the noise data caused by vibration during the filtering process, and retain the flow velocity data fluctuation caused by the sediment increase and decrease change, thereby improving the accuracy of the filtered flow velocity data and ensuring the accuracy of the meter reading of the intelligent ultrasonic water meter. Description of the Drawings

[0045] Figure 1 is the step flow chart of a meter reading method of an intelligent ultrasonic water meter of the present invention.

[0046] Figure 2 is the schematic block diagram of a computer device provided by an embodiment of the present invention. Detailed Embodiments

[0047] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention. The present invention will be described in detail below with reference to the drawings and specific embodiments.

[0048] It should be understood that when used in this specification, the terms "include" and "comprise" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0049] 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 this specification of the present invention, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0050] It should be further understood that the term " / and" used in this specification of the present invention refers to any combination and all possible combinations of one or more of the related listed items, and includes these combinations.

[0051] Embodiment 1

[0052] During the process of farmland irrigation, when the intelligent ultrasonic water meter collects flow velocity data, it will be affected by mechanical vibrations of large-scale mechanical equipment in the farmland, vibrations such as the operation of water pumps, etc., which may interfere with ultrasonic signals and cause abnormal fluctuations (i.e., noise data) in the flow velocity data. At the same time, the increase and decrease of sediment in the water pipe will also cause normal fluctuations in the flow velocity data (in this case, the fluctuations in the flow velocity data are normal fluctuations). If the flow velocity data is directly filtered, it is easy to filter out the flow velocity data of the normal fluctuations caused by the increase and decrease of sediment, reducing the accuracy of the collected data, and thus making the transmitted water meter readings untrustworthy.

[0053] In order to distinguish the influence of sediment in the water pipe and vibration on the data collection of the intelligent ultrasonic water meter and ensure the accuracy of the transmitted readings of the intelligent ultrasonic water meter, the present invention provides a method for reading the intelligent ultrasonic water meter. In this embodiment, the intelligent ultrasonic water meter is an instrument that measures the water flow rate by using the principle of ultrasonic wave propagation in water. It usually does not directly collect water flow rate data, but indirectly calculates the water flow rate by measuring the propagation speed of ultrasonic waves in water.

[0054] Specifically, a method for reading an intelligent ultrasonic water meter is as Figure 1As shown, the method includes the following steps:

[0055] Obtain the first flow velocity data sequence of the water pipe collected by the intelligent ultrasonic water meter within the first time interval at a certain opening degree of the water pipe outlet valve, and obtain the pressure category data sequence of the water pipe and the amplitude data of the water pipe within the first time interval;

[0056] According to the water flow velocity data and the fluctuating amplitude corresponding to each pressure category at the corresponding moment in the pressure category data sequence, obtain the fitting fluctuation curve segment of each pressure category in the second time interval;

[0057] Fuse the fitting fluctuation curve segments corresponding to all pressure categories to obtain the sediment increase and decrease change curve in the first time interval;

[0058] Combine the obtained pressure data sequence of the water pipe in the first time interval and the sediment increase and decrease change curve, and perform filtering processing on the first flow velocity data sequence;

[0059] Transmit the filtered flow velocity data sequence obtained by the filtering process to the target server, thereby completing the meter reading of the intelligent ultrasonic water meter.

[0060] According to the water flow velocity data and the fluctuating amplitude corresponding to each pressure category at the corresponding moment in the pressure category data sequence, the present invention obtains the fitting fluctuation curve segment of each pressure category in the second time interval; fuses the fitting fluctuation curve segments corresponding to all pressure categories to obtain the sediment increase and decrease change curve in the first time interval, so as to analyze the sediment increase and decrease change in the water pipe, and use it to remove the noise data caused by vibration during the filtering process, and retain the flow velocity data fluctuation caused by the sediment increase and decrease, thereby improving the accuracy of the filtered flow velocity data and ensuring the accuracy of the meter reading of the intelligent ultrasonic water meter.

[0061] In a specific embodiment, during the farmland irrigation process, use the intelligent ultrasonic water meter to obtain the first flow velocity data sequence of the water pipe collected within the first time interval at a certain opening degree of the water pipe outlet valve. At the same time, use a vibration sensor and a pressure sensor to collect the vibration data sequence and the pressure data sequence of the corresponding water pipe within the first time interval respectively. Among them, the collection frequency is 1 time per second.

[0062] It should be noted that during the entire process of each irrigation, the opening degree of the water pipe outlet valve remains unchanged. When it is necessary to change the opening degree of the valve, collect the first flow velocity data sequence, vibration data sequence and pressure data sequence at a certain fixed opening degree of the valve.

[0063] This is because when the opening degree of the valve of each water pipe remains unchanged and the cross-sectional area of the water pipe is the same, if the water pressure is also the same, then according to the basic principle of fluid mechanics, it can be known that without considering other influencing factors, the flow velocity should be the same.

[0064] 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 gradually decreases to the set lower threshold. At this time, the water pressure control system will activate the corresponding adjustment mechanism to increase the water pressure until the water pressure reaches the set upper threshold, and then the water pressure stops increasing. Due to continuous water use for 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, resulting in the water pressure in the water pipe showing fluctuating changes.

[0065] In this embodiment, obtaining the pressure category data sequence of the water pipe within the first time interval includes:

[0066] Obtaining the pressure data sequence of the water pipe within the first time interval;

[0067] Dividing the pressure data with the same pressure value into one category to obtain the pressure category data sequence of the water pipe .

[0068] Specifically, taking any one pipe as an example, from the start moment of irrigation to the current moment , within the first time interval , , dividing the pressure data with the same pressure value into one category to obtain the pressure category data sequence of this pipe, denoted as .

[0069] In a specific embodiment, obtaining the amplitude data of the water pipe within the first time interval includes:

[0070] Obtaining the vibration data sequence R of the water pipe within the first time interval , ;

[0071] According to the peaks and valleys in the vibration data sequence R, taking the sequence segment corresponding between adjacent peak points and valley points as a fluctuation, and dividing several fluctuations in the vibration data sequence R;

[0072] Using the difference between the maximum value and the minimum value in each fluctuation as the amplitude of each fluctuation;

[0073] Thus, obtaining the amplitude data of the water pipe.

[0074] In a specific embodiment, according to the water flow velocity data corresponding to each pressure category at the moment in the pressure category data sequence and the amplitude of the fluctuation, obtaining the fitting fluctuation curve segment of each pressure category in the second time interval includes:

[0075] According to the time sequence, count the water flow velocity data and the amplitude of the fluctuation corresponding to the moments of all pressure data in each pressure category, and obtain the second flow velocity data sequence and the amplitude data sequence corresponding to each pressure category data.

[0076] It is known that an increase in sediment in the water pipe usually leads to a decrease in the flow velocity under the same pressure. This is because the sediment will occupy part of the space of the water pipe channel, reducing the effective channel area of the water flow, thereby increasing the resistance of the water flow and the flow velocity also decreases accordingly (basic principle of fluid mechanics). And the sediment in the water pipe may gradually accumulate or decrease with the scouring of the water flow. Therefore, the change in the increase or decrease of sediment can be reflected by the change in the flow velocity under the same water pressure. It is known that an increase in sediment in the water pipe usually leads to a decrease in the flow velocity under the same pressure. This is because the sediment will occupy part of the space of the water pipe channel, reducing the effective channel area of the water flow, thereby increasing the resistance of the water flow and the flow velocity also decreases accordingly (basic principle of fluid mechanics). And the sediment in the water pipe may gradually accumulate or decrease with the scouring of the water flow. Therefore, the change in the increase or decrease of sediment can be reflected by the change in the flow velocity under the same water pressure.

[0077] Taking the pressure category as an example, among the moments of all pressure data with the pressure category being , count the flow velocity data at each moment and the amplitude data at each moment, and obtain the second flow velocity data sequence corresponding to the pressure category and the amplitude data sequence .

[0078] Count the mode in the amplitude data sequence, select the mode with the smallest amplitude, and calculate the weight corresponding to each water flow velocity data in the flow velocity data sequence .

[0079] Due to the influence of external vibration, it may interfere with the ultrasonic signal, resulting in abnormal fluctuations in the flow velocity data, that is, the appearance of noise data. Therefore, the present invention analyzes the flow velocity as much as possible in the flow velocity data sequence under the same vibration amplitude to reduce the influence of the change in vibration amplitude.

[0080] The present invention selects the mode with the smallest amplitude because there may be multiple modes, and selecting the mode with the smallest amplitude can ensure less vibration influence.

[0081] This embodiment also provides a calculation formula for the weight of the i-th flow velocity data in the flow velocity data sequence , which is:

[0082] ;

[0083] Wherein, is the i-th amplitude data in is a linear normalization function used to normalize the amplitude data to between 0 and 1; is the absolute value function; is the mode.

[0084] According to the weights of each water flow velocity data in the second water flow velocity data sequence, use the weighted least squares method to perform a fluctuation curve fitting on all the data in the second water flow velocity data sequence, and obtain the fitting fluctuation curve segments for each pressure category in the second time interval.

[0085] In this embodiment, the start time among the times when all the pressure data of the pressure category is obtained is , and the end time is .

[0086] According to the weights of each flow velocity data in the flow velocity data sequence , use the weighted least squares method to perform a fluctuation curve fitting on all the data in the flow velocity data sequence , and obtain the fitting fluctuation curve segment corresponding to the flow velocity data sequence . Among them, the horizontal axis of the fitting fluctuation curve segment is time, and the vertical axis is the flow velocity, and the fitting fluctuation curve segment is in the time interval , , on the horizontal axis.

[0087] If the flow velocity data increases in the fitting fluctuation curve segment , it indicates that the sediment decreases with the water flow scouring; if the flow velocity data decreases in the fitting fluctuation curve segment , it indicates that the sediment accumulates and increases.

[0088] Repeat the above steps to obtain the fitting fluctuation curve segments corresponding to each pressure category data in the pressure category data sequence A, and the fitting fluctuation curve segments are in the second time interval corresponding to the k-th pressure category data on the horizontal axis , .

[0089] In a specific embodiment, fuse the fitting fluctuation curve segments corresponding to all pressure categories to obtain the sediment increase and decrease change curve in the first time interval, including:

[0090] Calculate the credibility of the fitting fluctuation curve segments for each pressure category in the second time interval reflecting the sediment increase and decrease changes;

[0091] 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 where the target moment is located as the target fitting fluctuation curve segment;

[0092] Calculate the sediment deposition amount at the target moment according to the credibility of the sediment increase and decrease changes reflected by the target fitting fluctuation curve segment;

[0093] Repeat the above steps to obtain the sediment deposition amount at each moment within the first time interval, thereby forming a curve of sediment increase and decrease changes.

[0094] In a specific embodiment, calculating the credibility of the sediment increase and decrease changes reflected by the fitting fluctuation curve segment of each pressure category in the second time interval includes:

[0095] Obtain the third flow velocity data sequence within the second time interval;

[0096] Calculate the distribution suitability of the second flow velocity data sequence within the 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 differences corresponding to all adjacent two flow velocity data in the second flow velocity data sequence;

[0097] Obtain the data quantity in the amplitude data sequence, the maximum value and the minimum value in the amplitude data sequence, and calculate the credibility of the sediment increase and decrease changes reflected by the fitting fluctuation curve segment corresponding to each pressure category in combination with the quantity of the mode and the distribution suitability in the amplitude data sequence.

[0098] In this embodiment, taking the fitting fluctuation curve segment as an example, within the time interval , , the more data in the flow velocity data sequence , the more uniform the distribution, and the smaller the vibration interference, it indicates that the fitting fluctuation curve segment reflects the sediment increase and decrease changes within the time interval , more credibly.

[0099] Obtain the flow velocity data sequence , within the time interval , that is, the third flow velocity data sequence.

[0100] Then the formula for calculating the distribution suitability H of the flow velocity data sequence within the time interval , is:

[0101] ;

[0102] Wherein, is the number of data in the flow velocity data sequence ; is the number of data in the flow velocity data sequence ; is the variance of the time differences corresponding to all adjacent pairs of data in the flow velocity data sequence .

[0103] Since the proportion of the number of the flow velocity data sequence in the flow velocity data sequence is larger, is larger. The more uniformly the flow velocity data sequence is distributed in the flow velocity data sequence , when it is smaller, it indicates that the distribution suitability H of the flow velocity data sequence in the time interval , should be larger, thus ensuring the fitting credibility of the fitted fluctuation curve segment .

[0104] Then the calculation formula for the credibility degree that the fitted fluctuation curve segment reflects the increase and decrease changes of sediments is:

[0105] ;

[0106] Among them, is the number of the mode in the amplitude data sequence , is the number of data in the amplitude data sequence , , are respectively the maximum value and the minimum value in the amplitude data sequence .

[0107] Since the proportion of the mode in the amplitude data sequence is larger, and is smaller, it indicates that the number of the same amplitudes is larger and the amplitude change degree is smaller, that is, the vibration interference is smaller. Then the fitting reliability of the fitted fluctuation curve segment is higher. Thus, combined with the distribution suitability H, the credibility degree that the fitted fluctuation curve segment reflects the increase and decrease changes of sediments is obtained, and the larger it is, the more credible it is.

[0108] Similarly, for each pressure category in the pressure category data sequence , the fitted fluctuation curve segment corresponding to each pressure category data is obtained , and the time interval where the fitted fluctuation curve segment is located on the horizontal axis .

[0109] In a specific embodiment, according to the credibility of the target fitted fluctuation curve segment reflecting the increase or decrease of sediment, calculating the sediment deposition amount at the target moment includes:

[0110] According to the credibility of a certain target fitted fluctuation curve segment reflecting the increase or decrease of sediment, calculating the sum of the credibilities of all target fitted fluctuation curve segments reflecting the increase or decrease of sediment;

[0111] Combining the number of target fitted fluctuation curve segments, the water flow velocity value corresponding to the target moment on a certain target fitted fluctuation curve segment, the credibility of a certain target fitted fluctuation curve segment reflecting the increase or decrease of sediment, and the sum of the credibilities of all target fitted fluctuation curve segments reflecting the increase or decrease of sediment, calculating the sediment deposition amount at the target moment.

[0112] In this embodiment, within the time interval , , each pressure category in the pressure category data sequence is in the second time interval, denoted as . Taking as an example of the target moment, in , obtaining the fitted fluctuation curve segment corresponding to the time interval where exists as the target fitted fluctuation curve segment.

[0113] This embodiment provides the calculation formula for the sediment deposition amount at the moment as:

[0114] ;

[0115] Wherein, is the number of target fitted fluctuation curve segments, is the nth target fitted fluctuation curve segment at the target moment corresponding flow velocity value, is the credibility of the nth target fitted fluctuation curve segment reflecting the increase or decrease of sediment, is the sum of the credibilities of all target fitted fluctuation curve segments reflecting the increase or decrease of sediment, is a linear normalization function used to normalize the data value between 0 and 1.

[0116] Since The larger it is, the more credible the nth target fitting fluctuation curve segment is, and a larger weight is assigned. It is known that at the same pressure, a small flow rate indicates more sediment, and a large flow rate indicates less sediment. Therefore, take The inverse proportional value of represents the sediment deposition amount.

[0117] Similarly, the sediment deposition amounts at each moment within the time interval , are obtained, and a sediment increase and decrease change curve is formed.

[0118] In a specific embodiment, in combination with the pressure data sequence of the water pipe within the first time interval and the obtained sediment increase and decrease change curve, filtering processing is performed on the first flow rate data sequence, including:

[0119] Obtain the first flow rate data sequence and pressure data sequence of the first time interval;

[0120] Perform EMD decomposition on the first flow rate data sequence to obtain multiple IMF components;

[0121] According to the Pearson correlation coefficient between the pressure data sequence and each IMF component, and the Pearson correlation coefficient between the sediment increase and decrease change curve and each IMF component, calculate the reconstruction weight of each IMF component;

[0122] Perform weighted reconstruction of the EMD decomposition according to the reconstruction weight of each IMF component to obtain the filtered flow rate data sequence of the first flow rate data sequence.

[0123] In this embodiment, the first flow rate data sequence B of the time interval , and the pressure data sequence Z are obtained.

[0124] The present invention uses the EMD decomposition algorithm to perform filtering processing on the first flow rate data sequence B. The EMD decomposition algorithm is a well-known technology and will not be described in detail here. Using the EMD decomposition algorithm can separate the noise components and useful signal components in the signal.

[0125] Therefore, in the process of reconstructing the signal by the present invention, larger weights are assigned to important signal components to ensure the accuracy of the change trend of the flow rate data during the filtering and denoising process of the flow rate data, and the actual fluctuations of the flow rate data caused by the increase and decrease of the sediment in the water pipe are not filtered out.

[0126] In this embodiment, by performing EMD decomposition on the first flow rate data sequence B, multiple IMF components are obtained; generally, a residual component is also obtained.

[0127] Under ideal conditions, according to Bernoulli's law, 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.

[0128] Therefore, the data transformation trend of an IMF component representing the 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 the flow velocity data that changes with the increase or decrease of sediment should be negatively correlated with the trend of the increase or decrease of sediment.

[0129] Then the reconstruction weight of the j-th IMF component has the following calculation formula:

[0130] ;

[0131] where, is the Pearson correlation coefficient between the pressure data sequence and the j-th IMF component , is the Pearson correlation coefficient between the curve of the increase or decrease of sediment and the j-th IMF component .

[0132] Among them, the Pearson correlation coefficient is a well-known technology, rounded to be between -1 and 1. The closer it is to -1, the more the two data sequences conform to negative correlation. Therefore or is larger, the more the j-th IMF component conforms to the pressure change or the increase or decrease of sediment, that is, the more important it is, and a larger reconstruction weight is required.

[0133] It should be noted that since the value range of the Pearson correlation coefficient is between -1 and 1, the value range of the reconstruction weight is between 0 and 2. In order to make the sum of the reconstruction weights of all IMF components equal to 1, in this embodiment, the reconstruction weight is divided by the sum of the reconstruction weights of all IMF components to normalize the reconstruction weight . Thus, the reconstruction weight of each IMF component is obtained. Finally, according to the reconstruction weight of each IMF component, weighted reconstruction of EMD decomposition (this is a well-known operation) is performed to obtain the filtered flow velocity data sequence BL of the first flow velocity data sequence B.

[0134] In a specific embodiment, the filtered flow velocity data sequence obtained by filtering processing is transmitted to the target server, thereby completing the meter reading of the intelligent ultrasonic water meter.

[0135] In this embodiment, it is known that the working principle of the intelligent ultrasonic water meter is based on the fact that when ultrasonic waves propagate in a liquid, the flow of the liquid will cause changes in the propagation times of the downstream and upstream directions. This change is proportional to the flow velocity of the liquid. By calculating the difference in propagation times, the velocity of the liquid is obtained, and then the flow rate is calculated.

[0136] Specifically, the intelligent ultrasonic water meter calculates the flow velocity by measuring the propagation time difference of ultrasonic signals in the downstream and upstream directions. Since the propagation speed of the ultrasonic signal in the downstream direction is faster, while the propagation speed of the ultrasonic signal in the upstream direction is slower, by measuring the time difference between these two directions, the flow velocity of the fluid can be obtained. Finally, the flow rate of the fluid is calculated based on the product of the flow velocity and the cross-sectional area of the pipeline.

[0137] Therefore, according to the obtained filtered flow velocity data sequence BL, the present invention can obtain the flow rate data sequence of the water pipe, transmit the flow rate data sequence of the water pipe to the central server, and store it; or directly transmit the obtained filtered flow velocity data sequence BL to the central server, and then the central server calculates the flow rate data sequence of the water pipe and stores it. Thus, the meter reading of the intelligent ultrasonic water meter is accurately completed; or the obtained filtered flow velocity data sequence BL can be transmitted to the edge server for calculation to obtain the flow rate data sequence of the water pipe, and then the flow rate data sequence of the water pipe is transmitted to the central server and stored.

[0138] Please refer to Figure 2 , Figure 2 FIG. is a schematic block diagram of a computer device provided by an embodiment of the present invention. The computer device 500 is a server, and the server can be an independent server or a server cluster composed of multiple servers.

[0139] Refer to Figure 2 FIG., the computer device 500 includes a processor 502, a memory, and a network interface 505 connected through a system bus 501. Among them, the memory may include a non-volatile storage medium 503 and an internal memory 504.

[0140] 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 be caused to execute the meter reading method of the intelligent ultrasonic water meter.

[0141] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500.

[0142] 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 be caused to execute the meter reading method of the intelligent ultrasonic water meter.

[0143] The network interface 505 is used for network communication, such as providing data information transmission, etc. Those skilled in the art can understand that Figure 2 The structure shown in is only a block diagram of some structures 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 some components, or have different component arrangements.

[0144] Among them, 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 embodiments of the present invention.

[0145] Those skilled in the art can understand that Figure 2 The embodiments of the computer device shown in 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 those shown in the figure, or combine some components, or have different component arrangements. For example, in some embodiments, the computer device may only include a memory and a processor. In such an embodiment, the structures and functions of the memory and the processor are the same as those in Figure 2 the embodiment shown and will not be described in detail here.

[0146] It should be understood that in the embodiments 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 (DSPs), application specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs) 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.

[0147] 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, and when the computer program is executed by a processor, the meter reading method of the intelligent ultrasonic water meter disclosed in the embodiments of the present invention is implemented.

[0148] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described devices, apparatuses, and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein. Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described according to their functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians 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.

[0149] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, or units with the same function can be aggregated into one unit. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed couplings or direct couplings or communication connections to each other can be indirect couplings or communication connections through some interfaces, devices, or units, or can be electrical, mechanical, or other forms of connection.

[0150] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the objectives of the embodiments of the present invention.

[0151] In addition, the functional units in each embodiment of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0152] When 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 such understanding, the technical solution of the present invention, in essence, 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 and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), magnetic disks, or optical discs.

[0153] Obviously, the above-mentioned embodiments of the present invention are merely examples for clearly illustrating the present invention, rather than limitations on the implementation manners of the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall all be included within 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 velocity data sequence obtained by filtering is transmitted to the target server, thereby completing the meter reading of the intelligent ultrasonic water meter; 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 classified into one category to obtain the pressure category data sequence 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, 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.

2. 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.

3. 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.

4. The meter reading method of an intelligent ultrasonic water meter according to claim 3, 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.

5. The meter reading method of an intelligent ultrasonic water meter according to claim 3, 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.

6. 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.

7. A computer system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: 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 6 is implemented.

8. 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 6.

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