Intelligent non-magnetic water meter based on Internet of Things and counting method

Abstract

The invention discloses an intelligent non-magnetic water meter based on the Internet of Things and a counting method, and relates to the technical field of metering instruments, and the water meter structurally comprises a non-magnetic sensing structure used for collecting a corresponding electric signal when water flow is generated; the non-magnetic sensing structure is connected with the main control module and is used for processing the electric signal to obtain corresponding flow data; the monitoring module is connected with the main control module and is used for recording operation and data change of the water meter; the wireless communication module is connected with the main control module and the monitoring module and is used for realizing wireless transmission of flow data; according to the invention, the electric signal when the water flow is generated can be accurately collected, and the signal is processed and judged, so that reliable flow data is obtained, and the metering precision is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of metering instruments, and more specifically to an intelligent non-magnetic water meter based on the Internet of Things and a counting method. Background Art

[0002] Currently, non-magnetic water meters use the principle of electromagnetic induction to calculate the water consumption by measuring the water flow rate. When water flows through the non-magnetic water meter, it drives the turbine inside the meter to rotate. The turbine is connected to a magnetic sensor, and the rotation of the turbine causes the magnetic sensor to generate a changing magnetic field, thereby generating an electrical signal. The electrical signal is converted into the water consumption by the signal processing unit. The components that directly contact water and obtain signals in non-magnetic water meters have no magnetism and are not easily adsorbed by impurities in water. They can still accurately measure after long-term use. Therefore, non-magnetic water meters are increasingly favored by water meter manufacturers.

[0003] However, during the use of non-magnetic water meters, due to some external interferences, the measurement results are inaccurate and the data cannot be corrected. At the same time, due to some external interferences with human factors, the authenticity of the data collected by the water meter cannot be guaranteed. The prior art lacks the process of judging the authenticity of water meter data and data correction, and the detection accuracy is relatively low.

[0004] Therefore, how to provide an intelligent non-magnetic water meter and a counting method that can solve the above problems is an urgent problem for those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides an intelligent non-magnetic water meter based on the Internet of Things and a counting method, which accurately collects the electrical signal when water flow is generated, processes and judges the signal to obtain reliable flow data, and ensures the measurement accuracy.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] An intelligent non-magnetic water meter based on the Internet of Things, comprising:

[0008] A non-magnetic sensing structure for collecting the corresponding electrical signal when water flow is generated;

[0009] A main control module, the non-magnetic sensing structure is connected to the main control module for processing the electrical signal to obtain the corresponding flow data;

[0010] A monitoring module, the monitoring module is connected to the main control module for recording the operations and data changes of the water meter;

[0011] A wireless communication module, the wireless communication module is connected to the main control module and the monitoring module for realizing the wireless transmission of flow data.

[0012] Preferably, the non-magnetic sensing structure includes a first clock unit, an induction coil, and an output unit connected in sequence.

[0013] Preferably, the main control module includes:

[0014] A preprocessing unit, which is connected to the output unit and is used for preprocessing the electrical signal;

[0015] An analog-to-digital conversion unit, which is connected to the preprocessing unit and is used for performing analog-to-digital conversion on the preprocessed electrical signal to obtain a corresponding preliminary calculation result.

[0016] Preferably, the main control module further includes:

[0017] A prediction unit, which is connected to the preprocessing unit and is used for predicting the preprocessed electrical signal to obtain a corresponding prediction result;

[0018] A calculation unit, which is connected to the analog-to-digital conversion unit and the prediction unit and is used for judging the difference between the preliminary calculation result and the prediction result;

[0019] A judgment unit, which is connected to the calculation unit. A preset threshold is pre-set inside the judgment unit, and a judgment result is output.

[0020] Preferably, the main control module further includes:

[0021] A first instruction output unit, which is connected to the judgment unit and the wireless communication module and is used for outputting the preliminary calculation result at this time when the difference is less than the preset threshold;

[0022] A second instruction output unit, which is connected to the judgment unit and the wireless communication module and is used for calling the monitoring data of the monitoring module at the corresponding moment for processing when the difference is greater than or equal to the preset threshold.

[0023] Preferably, the monitoring module includes:

[0024] An acquisition unit, which is used for acquiring the monitoring data of the water meter;

[0025] A processing unit, which is connected to the acquisition unit and the second instruction output unit and is used for processing the monitoring data and determining whether there is an abnormal behavior according to the processing result;

[0026] A third instruction processing unit, which is connected to the processing unit and is used for notifying the staff of the processing result and the preliminary calculation result through the wireless communication module when the processing result shows an abnormal behavior.

[0027] Preferably, the monitoring module further includes:

[0028] A fourth instruction processing unit, which is connected to the processing unit and is used to correct the preliminary calculation result when there is no abnormal behavior in the processing result.

[0029] The present invention also provides a metering method for an intelligent non-magnetic water meter based on the Internet of Things, including the following steps:

[0030] Collect the corresponding electrical signal when water flow is generated through a non-magnetic sensing structure;

[0031] Process the electrical signal through the main control module to obtain the corresponding preliminary calculation result, and determine whether there is an abnormality in the preliminary calculation result;

[0032] If the main control module determines that the flow data is abnormal, call the monitoring data of the monitoring module and process it;

[0033] When there is an abnormality in the processing result of the monitoring data, send the processing result and the preliminary calculation result to the staff through the wireless communication module;

[0034] When there is no abnormality found in the processing result of the monitoring data, correct the preliminary calculation result.

[0035] As can be seen from the above technical solutions, compared with the prior art, the present invention discloses an intelligent non-magnetic water meter and a counting method based on the Internet of Things, having the following beneficial effects:

[0036] 1. The non-magnetic sensing structure provided by the present invention can accurately collect the electrical signal when water flow is generated, and through the processing, conversion and judgment of the main control module, reliable flow data is obtained, ensuring the metering accuracy.

[0037] 2. The monitoring module provided by the present invention can record the operations and data changes of the water meter. Once the processing unit determines that there is an abnormal behavior, it notifies the staff in time to ensure the normal operation of the water meter;

[0038] 3. The prediction unit provided by the present invention predicts the electrical signal, compares it with the preliminary calculation result after analog-to-digital conversion, and the judgment unit decides to output the preliminary calculation result or call the monitoring data for processing according to the relationship between the difference and the preset threshold, improving the accuracy and reliability of the data.

[0039] 4. When there is no abnormality in the processing result of the monitoring data, the present invention can correct the preliminary calculation result, further improving the data accuracy and providing a more accurate basis for subsequent water use management and billing. Description of the Drawings

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on the provided drawings.

[0041] Figure 1 It is a structural principle block diagram of an intelligent non-magnetic water meter based on the Internet of Things provided by the present invention. Specific embodiments

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0043] See Figure 1 As shown, the embodiments of the present invention disclose an intelligent non-magnetic water meter based on the Internet of Things, including:

[0044] A non-magnetic sensing structure 1 for collecting the corresponding electrical signal when water flow is generated;

[0045] A main control module 2, the non-magnetic sensing structure 1 is connected to the main control module 2, for processing the electrical signal to obtain the corresponding flow data;

[0046] A monitoring module 3, the monitoring module 3 is connected to the main control module 2, for recording the operations and data changes of the water meter;

[0047] A wireless communication module 4, the wireless communication module 4 is connected to the main control module 2 and the monitoring module 3, for realizing the wireless transmission of flow data, where the wireless communication module 4 can be implemented through the NB-IoT network. The NB-IoT network supports the efficient connection of devices with long standby time and high requirements for network connection.

[0048] In a specific embodiment, the non-magnetic sensing structure 1 includes a first clock unit 11, an induction coil 12, and an output unit 13 connected in sequence. Among them, the induction coil 12 can include multiple-stage excitation coils, and the output unit 13 can measure by detecting the change of the induced electromotive force in the coil. The first clock unit 11 can obtain the acquisition time corresponding to the electrical signal output by the output unit 13.

[0049] In a specific embodiment, the main control module 2 includes:

[0050] The preprocessing unit 21 is connected to the output unit 13 and is used for preprocessing the electrical signal. The preprocessing process may include processes such as missing value processing, filtering, and amplification, which can preliminarily process the electrical signal and is a key process for subsequent data analysis.

[0051] The analog-to-digital conversion unit 22 is connected to the preprocessing unit 21 and is used for performing analog-to-digital conversion on the preprocessed electrical signal to obtain the corresponding preliminary calculation result. The analog-to-digital conversion unit 22 can be implemented through a pre-calibrated linear relationship between the electrical signal and the flow rate.

[0052] In a specific embodiment, the main control module 2 further includes:

[0053] The prediction unit 23 is connected to the preprocessing unit 21 and is used for predicting the preprocessed electrical signal to obtain the corresponding prediction result.

[0054] The calculation unit 24 is connected to the analog-to-digital conversion unit 22 and the prediction unit 23 and is used for judging the difference between the preliminary calculation result and the prediction result.

[0055] The judgment unit 25 is connected to the calculation unit 24. A preset threshold is pre-set inside the judgment unit 25, and the judgment result is output.

[0056] Specifically, the prediction unit 23 can be implemented using an LSTM neural network model and an RNN neural network, which can better predict the electrical signal.

[0057] In a specific embodiment, the main control module 2 further includes:

[0058] The first instruction output unit 26 is connected to the judgment unit 25 and the wireless communication module 4 and is used for outputting the preliminary calculation result at this time when the difference is less than the preset threshold.

[0059] The second instruction output unit 27 is connected to the judgment unit 25 and the wireless communication module 4 and is used for calling and processing the monitoring data of the monitoring module 3 at the corresponding moment when the difference is greater than or equal to the preset threshold.

[0060] In a specific embodiment, the monitoring module 3 includes:

[0061] The acquisition unit 31 is used for acquiring the monitoring data of the water meter. The monitoring data may include various types of monitoring data such as video data acquired by an industrial camera and proximity data acquired by a proximity sensor.

[0062] The processing unit 32 is connected to the acquisition unit 31 and the second instruction output unit 27, and is used to process the monitoring data and determine whether there is any abnormal behavior according to the processing result;

[0063] The third instruction processing unit 33 is connected to the processing unit 32, and is used to notify the staff of the processing result and the preliminary calculation result through the wireless communication module 4 when there is abnormal behavior in the processing result.

[0064] Specifically, when the difference is greater than or equal to the preset threshold, the processing unit 32 processes the monitoring data within the preset range before and after the acquisition time corresponding to the first clock unit 11. The processing unit 32 can implement data processing through a preset processing model (such as a convolutional neural network model) and determine whether there is any abnormal behavior according to the processing result.

[0065] In a specific embodiment, the monitoring module 3 further includes:

[0066] The fourth instruction processing unit 34 is connected to the processing unit 32, and is used to correct the preliminary calculation result when there is no abnormal behavior in the processing result.

[0067] Specifically, the specific processing process of the fourth instruction processing unit 34 further includes:

[0068] Retrieve the historical time data corresponding to the acquisition time of the water meter corresponding to the first clock unit 11 through big data, and compare whether there is a large difference between the two. If the difference range is within the preset range, perform weighted fusion processing on the two according to the preset weights of the preliminary calculation result and the prediction result to obtain the final measurement result, so as to achieve the purpose of correcting the preliminary calculation result.

[0069] If the difference range exceeds the preset range, discard the preliminary calculation result and the prediction result, and send the specific analysis result to the staff through the wireless communication module 4 for processing. Through the above process, the embodiment of the present invention can further determine whether there is any abnormality in the data and improve the accuracy of data processing.

[0070] The embodiment of the present invention also provides a metering method for an intelligent non-magnetic water meter based on the Internet of Things according to any one of the above embodiments, including the following steps:

[0071] Collect the corresponding electrical signal when water flow is generated through the non-magnetic sensing structure 1;

[0072] Process the electrical signal through the main control module 2 to obtain the corresponding preliminary calculation result, and judge whether there is any abnormality in the preliminary calculation result;

[0073] If the main control module 2 determines that the flow data is abnormal, it calls the monitoring data of the monitoring module 3 and processes it;

[0074] When the processing result of the monitoring data is abnormal, the processing result and the preliminary calculation result are sent to the staff through the wireless communication module 4;

[0075] When no abnormality is found in the processing result of the monitoring data, the preliminary calculation result is corrected.

[0076] Specifically, when the main control module 2 determines that the flow data is abnormal, it calls the monitoring module 3 to process the monitoring data within a preset range before and after the acquisition time corresponding to the first clock unit 11 and processes it;

[0077] When the processing result indicates no abnormal behavior, the preliminary calculation result is sent through the wireless communication module 4; when the processing result indicates an abnormal behavior, the historical time data corresponding to the acquisition time of the water meter at the first clock unit 12 is retrieved through big data, and whether the difference between the two is large is compared. If the difference range is within the preset range, according to the preset weights of the preliminary calculation result and the prediction result, the two are weighted and fused to obtain the final measurement result. If the difference range exceeds the preset range, the preliminary calculation result and the prediction result are discarded, and the specific analysis result is sent to the staff through the wireless communication module 4 for processing.

[0078] In this specification, the various embodiments are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0079] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent non-magnetic water meter based on the Internet of Things, characterized in that Including: A non-magnetic sensing structure (1) for collecting corresponding electrical signals when water flow is generated; A main control module (2), the non-magnetic sensing structure (1) is connected to the main control module (2) for processing the electrical signals to obtain corresponding flow data; A monitoring module (3), the monitoring module (3) is connected to the main control module (2) for recording the operations and data changes of the water meter; A wireless communication module (4), the wireless communication module (4) is connected to the main control module (2) and the monitoring module (3) for realizing wireless transmission of flow data.

2. The intelligent non-magnetic water meter based on the Internet of Things according to claim 1, characterized in that, The non-magnetic sensing structure (1) includes a first clock unit (11), an induction coil (12), and an output unit (13) connected in sequence.

3. The intelligent non-magnetic water meter based on the Internet of Things according to claim 2, characterized in that, The main control module (2) includes: A preprocessing unit (21), the preprocessing unit (21) is connected to the output unit (13) for preprocessing the electrical signals; An analog-to-digital conversion unit (22), the analog-to-digital conversion unit (22) is connected to the preprocessing unit (21) for performing analog-to-digital conversion on the preprocessed electrical signals to obtain corresponding preliminary calculation results.

4. The intelligent non-magnetic water meter based on the Internet of Things according to claim 3, characterized in that, The main control module (2) further includes: A prediction unit (23), the prediction unit (23) is connected to the preprocessing unit (21) for predicting the preprocessed electrical signals to obtain corresponding prediction results; A calculation unit (24), the calculation unit (24) is connected to the analog-to-digital conversion unit (22) and the prediction unit (23) for judging the difference between the preliminary calculation result and the prediction result; A judgment unit (25), the judgment unit (25) is connected to the calculation unit (24), and a preset threshold is preset inside the judgment unit (25) and a judgment result is output.

5. The intelligent non-magnetic water meter based on the Internet of Things according to claim 4, characterized in that The main control module (2) further includes: A first instruction output unit (26), the first instruction output unit (26) is connected to the judgment unit (25) and the wireless communication module (4) for outputting the preliminary calculation result at this time when the difference is less than the preset threshold; A second instruction output unit (27), the second instruction output unit (27) is connected to the judgment unit (25) for calling the monitoring data of the monitoring module (3) at the corresponding moment for processing when the difference is greater than or equal to the preset threshold.

6. The intelligent non-magnetic water meter based on the Internet of Things according to claim 5, characterized in that, The monitoring module (3) includes: A collection unit (31) for collecting monitoring data of the water meter; A processing unit (32), the processing unit (32) is connected to the collection unit (31) and the second instruction output unit (27) for processing the monitoring data and determining whether there is an abnormal behavior according to the processing result; A third instruction processing unit (33), the third instruction processing unit (33) is connected to the processing unit (32) for notifying the staff of the processing result and the preliminary calculation result through the wireless communication module (4) when the processing result has an abnormal behavior.

7. The intelligent non-magnetic water meter based on the Internet of Things according to claim 6, wherein The monitoring module (3) further includes: A fourth instruction processing unit (34), the fourth instruction processing unit (34) being connected to the processing unit (32) and being configured to correct the preliminary calculation result when there is no abnormal behavior in the processing result.

8. A metering method of an intelligent non-magnetic water meter based on the Internet of Things according to any one of claims 1-7, characterized in that, The method includes the following steps: Collecting an electrical signal corresponding to a water flow rate through a magnetic-free sensing structure (1); Processing the electrical signal by a main control module (2) to obtain a corresponding preliminary calculation result and determining whether there is an abnormality in the preliminary calculation result; If the main control module (2) determines that the flow rate data is abnormal, calling the monitoring data of the monitoring module (3) and processing it; When there is an abnormality in the processing result of the monitoring data, sending the processing result and the preliminary calculation result to a staff member through a wireless communication module (4); When no abnormality is found in the processing result of the monitoring data, correcting the preliminary calculation result.

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