High-precision electromagnetic water meter system based on self-adaptive algorithm and measuring method of high-precision electromagnetic water meter system

Abstract

The invention discloses a high-precision electromagnetic water meter system based on an adaptive algorithm and a measuring method thereof, and relates to the technical field of water meters, the high-precision electromagnetic water meter system comprises a signal acquisition unit, a signal processing and adaptive unit, a data processing and control unit, an abnormity early warning unit, a communication and data management unit and a system operation, maintenance and optimization unit. According to the system, electric signals are subjected to amplification, filtering and analog-to-digital conversion processing, strong signal overload can be avoided, various noise interferences can be removed, electromagnetic interferences in data transmission are reduced, stability during data transmission is guaranteed, fluctuation and distortion of the signals are reduced, an algorithm is automatically matched through an algorithm matching module, and the accuracy of data transmission is improved. The dynamic adjustment and continuous processing module is used for dynamically adjusting parameters and continuously processing signals, so that the parameter adjustment and the signal processing are interlaced to form a cyclic optimization process, the signal processing effect is continuously improved, errors of measured data are reduced, and high-precision measurement of micro flow is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of water meters, and in particular to a high-precision electromagnetic water meter system based on an adaptive algorithm and a measurement method thereof. Background Art

[0002] Electromagnetic water meter is a flow measurement instrument developed based on Faraday's law of electromagnetic induction. It is used to accurately measure the volume flow of conductive liquids in closed pipes and is widely used in industrial and domestic water metering.

[0003] For example, Chinese patent CN209727177U discloses an electromagnetic water meter micro-flow measurement system, including a measuring tube, a microprocessor, an electromagnetic sensor, an excitation circuit, a signal processing module, a memory and a wireless transmission module. The electromagnetic sensor is installed on the measuring tube. The electromagnetic sensor includes an excitation input end and a signal output end. The excitation circuit is connected to the excitation input end, the signal output end is connected to the signal processing module, the microprocessor is respectively connected to the signal processing module and the excitation circuit, and also includes a temperature sensor a, the temperature sensor a is connected to the electromagnetic sensor, and the signal output end of the temperature sensor is connected to the microprocessor.

[0004] In the above patent, the temperature of the medium is measured in real time to solve the problem that the measured flow rate of most electromagnetic flow meters is too large and does not meet the requirements of electromagnetic water meters. However, when the system is in use, external electromagnetic interference will be superimposed on the measurement signal of the electromagnetic water meter, causing the measurement signal to fluctuate and distort, resulting in large errors in the measurement data of small flow rates, and the inability to accurately measure small flows. Summary of the invention

[0005] The purpose of the present invention is to provide a high-precision electromagnetic water meter system and a measurement method based on an adaptive algorithm, so as to solve the problem raised in the above background technology that when the system is in use, external electromagnetic interference will be superimposed on the electromagnetic water meter measurement signal, causing the measurement signal to fluctuate and distort, resulting in large errors in the small flow measurement data and the inability to accurately measure the small flow.

[0006] To achieve the above-mentioned object, the present invention provides the following technical solutions: a high-precision electromagnetic water meter system based on an adaptive algorithm, comprising a signal acquisition unit, a signal processing and adaptive unit, a data processing and control unit, an abnormal warning unit, a communication and data management unit, and a system operation and optimization unit; The signal acquisition unit collects the induced electromotive force signal generated by the water flow in real time through the electrode sensor, and transmits it to the signal processing and adaptive unit through a wired connection; the signal processing and adaptive unit amplifies, filters and performs analog-to-digital conversion on the electrical signal to obtain a digital signal, and dynamically adjusts the processing parameters of the digital signal; The signal processing and adaptive unit includes an algorithm matching module, a parameter setting and preliminary processing module, and a dynamic adjustment and continuous processing module. The algorithm matching module is used to select the LMS algorithm or the RLS algorithm according to the sensor type, fluid characteristics, and the environment. The parameter setting and preliminary processing module is used to set the initial parameters, perform preliminary processing on the collected electrical signals, and complete signal amplification, filtering and analog-to-digital conversion; The dynamic adjustment and continuous processing module continuously monitors the characteristics of electrical and digital signals through LMS or RLS algorithms, and calculates and adjusts parameters in real time; The data processing and control unit uses a microprocessor to complete system control, data processing and execution of adaptive algorithms; the abnormal warning unit is used to detect whether there are abnormalities in sensor status, signal quality and network communication conditions; the communication and data management unit is used to select a matching communication method based on the actual usage scenario; the system operation and optimization unit is used to detect system operation data and user needs, and optimize the adaptive algorithm.

[0007] Preferably, in the dynamic adjustment and continuous processing module, when it is detected that the change in the water flow velocity causes the change in the amplitude of the induced electromotive force signal, the algorithm automatically adjusts the amplification factor or the filtering parameters.

[0008] Preferably, the abnormal warning unit includes a data monitoring module, a sensor detection module, a warning response module and an abnormal proofreading module; The data monitoring module is used to monitor the signal quality and network communication data. When there is an abnormality in the data, the abnormal data is transmitted to the abnormality correction module; The sensor detection module is used to detect the sensor status. If the sensor fails, an abnormal signal is sent to the abnormal calibration module in time; The early warning response module is used to trigger the preset alarm mechanism and send an alarm signal to the control terminal; The abnormality proofreading module checks the abnormal data, determines the authenticity of the abnormal signal, and transmits the judgment result to the early warning response module.

[0009] Preferably, in the abnormality proofreading module, when proofreading abnormal data, the following contents are also included: A1. Data feature proofreading: Use statistical methods to calculate the mean and standard deviation of historical data, and then judge abnormal data based on the trend of data changes over time; A2. Sensor performance check: Calibrate the sensor regularly, compare the data before and after calibration, set up multiple redundant sensors to measure the same physical quantity, compare their data, and complete the sensor performance check; A3. Measurement environment assessment: By checking the environmental conditions during measurement and the operating status of the equipment related to the sensor, determine whether the surrounding environment and equipment interfere with the data; A4. Determine the logical relationship of data: Analyze the correlation between abnormal data and other related data, and determine the rationality of the data based on the laws of physics.

[0010] Preferably, the communication and data management unit includes a communication mode selection module, a storage and backup module and an automatic data upload module; The communication mode selection module is used to set the current usage scenario and automatically match the communication mode according to the usage scenario requirements; The storage and backup module is used to store the measured data in the local database and automatically back it up when the communication fails; After communication is restored, the automatic data upload module automatically uploads data to the system's cloud database to synchronize system data.

[0011] Preferably, when the communication mode is automatically matched according to the usage scenario requirements in the communication mode selection module, for areas with weak signals, low-power, long-distance NB-IoT or LoRa communication is selected, and for close distances and scenarios with high data transmission rate requirements, Bluetooth or Wi-Fi communication is selected.

[0012] Preferably, the system operation and optimization unit includes a monitoring and diagnosis module, a maintenance instruction generation module, a data management module and an algorithm optimization module. The monitoring and diagnosis module is used to collect various operation data of the water meter system in real time, and analyze the collected data using a fault diagnosis algorithm and an expert system; The maintenance instruction generation module automatically generates corresponding maintenance instructions based on the diagnosis results in the monitoring and diagnosis module, and sends the instructions to the terminal device of the maintenance personnel; The data management module is used to store, back up, retrieve and analyze data during system operation; The algorithm optimization module uses machine learning technology to train historical data and adjust the parameters of the algorithm.

[0013] Preferably, in the monitoring and diagnosis module, the fault diagnosis algorithm is based on statistical analysis and machine learning technology to extract features and recognize patterns in the data to determine whether there is a fault in the system and the type and location of the fault. The expert system stores the experience and knowledge of domain experts in the form of rules in the knowledge base, and matches and infers the monitoring data through the inference engine to draw diagnostic conclusions.

[0014] A measurement method for a high-precision electromagnetic water meter system based on an adaptive algorithm comprises the following steps: S1, initialization and parameter setting: After the system is started, the sensor calibration and initialization operations are first performed to set the initial parameters of the adaptive algorithm; S2, data acquisition and processing: The sensor collects the induced electromotive force signal generated by the water flow in real time and transmits it to the signal processing and adaptive unit to process the electrical signal. The adaptive algorithm dynamically adjusts the electrical signal processing parameters according to the real-time collected signal characteristics, environmental parameters and historical data; S3, flow calculation and error correction: The microprocessor calculates the water flow rate based on the processed digital signal using the built-in flow calculation model. During the calculation process, the microprocessor combines the parameters adjusted by the adaptive algorithm and considers the influence of temperature and pressure factors on fluid conductivity and density to perform real-time error correction. S4, data storage and transmission: the calculated flow data is stored in real time, and according to the set communication mode and adaptive communication strategy, the data is transmitted to the remote monitoring center and the abnormal warning unit. The abnormal warning unit determines whether there is abnormal data. If there is no abnormal data, the measurement data of the current system is output; S5. System monitoring and adaptive adjustment: The system continuously monitors the sensor status, signal quality and network communication. Once an abnormal situation is found, the adaptive algorithm immediately starts the emergency processing procedure and adjusts the system working mode. At the same time, based on the monitoring data, the adaptive algorithm continuously optimizes the system parameters and performs adaptive adjustments.

[0015] Preferably, in S3, the built-in traffic calculation model is: Where v is the average flow velocity of water perpendicular to the direction of the magnetic field, r is the inner diameter of the measuring tube, e is the induced electromotive force, q is the magnetic field strength, and L is the flow rate.

[0016] When calculating the water flow, the following contents are also included: S31, obtaining induced electromotive force: using a sensor to collect the induced electromotive force signal generated by the water flow in real time, and the signal processing and adaptive unit amplifies, filters and performs analog-to-digital conversion on the collected electrical signal to obtain the induced electromotive force in the form of a stable and accurate digital signal; S32, determining magnetic field strength and pipe parameters: in the initialization and parameter setting stage, according to the installation environment and expected measurement range of the water meter, set a suitable excitation current to determine the magnetic field strength, wherein the inner diameter of the measuring pipe is an inherent parameter of the water meter; S33, calculating flow velocity and flow rate: after obtaining the induced electromotive force, magnetic field strength and inner diameter parameters of the measuring tube, the processor in the data processing and control unit calculates the flow velocity of the water flow according to the flow calculation formula, and then obtains the water flow rate; S34. Consider error correction factors: In the process of flow calculation, the temperature and pressure factors of the fluid are considered to perform real-time error correction in combination with the parameters adjusted by the adaptive algorithm to compensate for the measurement error caused by temperature changes.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, the electrical signal is preliminarily processed by the parameter setting and preliminary processing module, so that the signal is amplified, filtered and processed by analog-to-digital conversion, which can avoid strong signal overload and remove various noise interferences, thereby reducing electromagnetic interference in data transmission, ensuring the stability of data transmission, reducing the fluctuation and distortion of digital signals, automatically matching the algorithm through the algorithm matching module, dynamically adjusting the parameters and continuously processing the signal through the dynamic adjustment and continuous processing module, so that the parameter adjustment and signal processing are intertwined to form a cyclic optimization process, so as to continuously improve the signal processing effect and reduce the error of the measurement data, thereby realizing high-precision measurement of small flow; 2. In the present invention, the operating data of the system is detected by the data monitoring module, and the use status of the sensor in the water meter is detected by the sensor detection module to determine whether the sensor is damp and water-intake or working abnormally. The detection results of the data monitoring module and the sensor detection module are input into the abnormal proofreading module for proofreading to determine the authenticity of the abnormal data. When the abnormal data is true, the alarm mechanism preset in the early warning response module is triggered in time to send an alarm signal to the control terminal, so that the staff can repair the system and equipment in time to ensure the normal use of the system and equipment; 3. In the present invention, the collected data is analyzed by the monitoring and diagnosis module using the fault diagnosis algorithm and the expert system, the maintenance instruction generation module can generate corresponding maintenance instructions according to the diagnosis results in the monitoring and diagnosis module, the algorithm optimization module can adjust the parameters of the algorithm to achieve the optimization of the algorithm, and the maintenance operation is performed through the timely diagnosis and positioning guidance of the fault, thereby improving the equipment maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A system block diagram of a high-precision electromagnetic water meter system based on an adaptive algorithm according to the present invention; Figure 2 This is a system diagram of a communication and data management unit of a high-precision electromagnetic water meter system based on an adaptive algorithm according to the present invention; Figure 3 This is a system diagram of system operation and maintenance and optimization unit of a high-precision electromagnetic water meter system based on an adaptive algorithm according to the present invention; Figure 4 The present invention is a flow chart of a high-precision electromagnetic water meter system based on an adaptive algorithm.

[0019] In the figure: 1. Signal acquisition unit; 2. Signal processing and adaptive unit; 21. Algorithm matching module; 22. Parameter setting and preliminary processing module; 23. Dynamic adjustment and continuous processing module; 3. Data processing and control unit; 4. Abnormal warning unit; 41. Data monitoring module; 42. Sensor detection module; 43. Warning response module; 44. Abnormal proofreading module; 5. Communication and data management unit; 51. Communication mode selection module; 52. Storage and backup module; 53. Automatic data upload module; 6. System operation and optimization unit; 61. Monitoring and diagnosis module; 62. Maintenance instruction generation module; 63. Data management module; 64. Algorithm optimization module. DETAILED DESCRIPTION

[0020] 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 implementation regulations described are only 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.

[0021] Example 1: Reference Figure 1-Figure 4 As shown, a high-precision electromagnetic water meter system based on an adaptive algorithm includes a signal acquisition unit 1, a signal processing and adaptive unit 2, a data processing and control unit 3, an abnormal warning unit 4, a communication and data management unit 5 and a system operation and optimization unit 6.

[0022] The signal acquisition unit 1 collects the induced electromotive force signal generated by the water flow in real time through the electrode sensor, and transmits it to the signal processing and adaptive unit 2 through a wired connection; The signal processing and adaptive unit 2 is used to amplify, filter and perform analog-to-digital conversion on the electrical signal to obtain a digital signal, and dynamically adjust the digital signal processing parameters. The signal processing and adaptive unit 2 integrates functional modules such as signal amplification, filtering, and analog-to-digital conversion. When the parameter setting and preliminary processing module 22 performs preliminary processing on the electrical signal, in the signal amplification link, an adaptive gain control algorithm is used to automatically adjust the amplification factor according to the strength of the induced electromotive force collected by the sensor to ensure that weak electrical signals can be effectively amplified while avoiding overload of strong signals. The filtering part adopts an adaptive filtering algorithm to monitor and remove various noise interferences in real time, such as power frequency interference and electromagnetic radiation interference. The analog-to-digital conversion module uses a high-precision A / D converter, and the electrical signal can obtain a digital signal after analog-to-digital conversion.

[0023] The signal processing and adaptive unit 2 includes an algorithm matching module 21, a parameter setting and preliminary processing module 22 and a dynamic adjustment and continuous processing module 23. The algorithm matching module 21 is used to select the LMS or RLS algorithm according to the sensor type, the measured fluid characteristics and the environment. When the algorithm matching module 21 is used for algorithm matching, if the electromagnetic water meter is used to measure the water flow with small conductivity fluctuation and relatively stable interference, the LMS algorithm can be selected; if the measurement environment is complex and the conductivity changes greatly, the RLS algorithm has more advantages due to its ability to quickly track time-varying parameters.

[0024] The parameter setting and preliminary processing module 22 is used to initialize the algorithm parameters, set the initial parameters according to the system experience, theoretical calculations or previous experimental data, and then use the LMS or RLS algorithm to perform preliminary processing on the collected electrical signals to complete signal amplification, filtering and analog-to-digital conversion. In this process, the quality of the digital signal after preliminary processing will be fed back to the evaluation of the algorithm parameters. If the digital signal processing effect is not good, such as the noise suppression is not obvious and the measurement accuracy does not meet expectations, it is necessary to re-examine the rationality of the parameter setting.

[0025] The dynamic adjustment and continuous processing module 23 automatically adjusts various parameters of the system according to the real-time collected water flow data, sensor status and environmental parameters, such as temperature and pressure, to achieve optimized control of the measurement process. In the signal processing process of the dynamic adjustment and continuous processing module 23, parameter adjustment and digital signal processing are intertwined. Each parameter adjustment will affect the digital signal processing result, and the new electrical signal and digital signal characteristics will prompt the algorithm to further adjust the parameters, forming a cyclic optimization process to continuously improve the processing effect of the digital signal and achieve high-precision measurement. The LMS or RLS algorithm is used to continuously monitor the characteristics of the electrical signal and the digital signal after analog-to-digital conversion, such as the amplitude, frequency and phase changes of the signal in the electromagnetic water meter system, and the parameters are calculated and adjusted in real time. When it is detected that the water flow velocity changes and causes the induced electromotive force signal amplitude to change, the algorithm automatically adjusts the amplification factor or filtering parameters.

[0026] The data processing and control unit 3 uses a high-performance microprocessor, which is responsible for the overall control of the system, data processing and execution of the adaptive algorithm. It analyzes and calculates the digital signal processed by the signal processing and adaptive unit 2, and combines the adaptive algorithm to adjust the sensor's excitation parameters, signal acquisition frequency and data processing method in real time according to the water flow state, fluid characteristics and environmental changes. When a large change in water flow velocity is detected, the acquisition frequency is automatically increased to ensure measurement accuracy. When a change in fluid conductivity is found, the excitation current is adjusted to ensure a stable output of the induced electromotive force.

[0027] The abnormal warning unit 4 is used to detect the sensor status, signal quality and network communication status, and to perform calibration and warning when an abnormality occurs; The abnormal warning unit 4 includes a data monitoring module 41, a sensor detection module 42, a warning response module 43 and an abnormal proofreading module 44; the data monitoring module 41 is used to monitor the quality of digital signals and network communication data. When the data is abnormal, the abnormal data is transmitted to the abnormal proofreading module 44; the sensor detection module 42 is used to detect the sensor state. If the sensor fails, an abnormal signal is sent to the abnormal proofreading module 44 in time; the warning response module 43 is used to trigger a preset alarm mechanism and send an alarm signal to the control terminal; the abnormal proofreading module 44 checks the abnormal data, determines the authenticity of the abnormal signal, and transmits the judgment result to the warning response module 43. If the abnormal signal is not true, the Z-score is used to detect the sensor state. The data is corrected and the corrected data is judged as abnormal again until the data is no longer abnormal and can be output as correct measurement data. The system continuously monitors parameters such as sensor status, signal quality, network communication status, and battery power. Once an abnormal situation is found, such as sensor failure, severe signal interference, network interruption, etc., the adaptive algorithm immediately starts the emergency processing procedure and adjusts the system working mode, such as switching backup sensors, changing the communication method, or reducing system power consumption, to ensure the normal operation of the system.

[0028] When checking abnormal data, the following contents are also included: 1. Data feature proofreading: Use statistical methods to calculate the mean and standard deviation of historical data, and then judge abnormal data based on the trend of data changes over time; 2. Sensor performance check: Calibrate the sensor regularly, compare the data before and after calibration, set up multiple redundant sensors to measure the same physical quantity, compare their data, and complete the sensor performance check; 3. Measurement environment assessment: By checking the environmental conditions during measurement and the operating status of the equipment related to the sensor, determine whether the surrounding environment and equipment interfere with the data; 4. Determine the logical relationship of data: Analyze the correlation between abnormal data and other related data, and determine the rationality of the data based on the laws of physics.

[0029] If the abnormal data deviates from the mean by more than a certain multiple of the standard deviation, it may be an outlier. Under normal circumstances, the flow data of the electromagnetic water meter should show a certain change pattern, such as an increase in peak flow and a decrease in valley flow. If the data shows a sudden change that is contrary to the trend, there may be a problem; If abnormal data still appears after calibration, it may be a sensor hardware failure. When setting up multiple redundant sensors to measure the same physical quantity, if only one sensor data is abnormal and the others are normal, then the abnormal data is likely to be untrue. Install multiple electromagnetic water meter sensors at important measuring points. If one shows an abnormal flow rate while the other data are similar, it can be preliminarily determined that the abnormal data is incorrect.

[0030] The flow data of electromagnetic water meters is correlated to the number of water-using equipment and pressure. If the flow increases abnormally but the number of water-using equipment does not increase and the pressure does not change significantly, then the flow data may be abnormal. In electromagnetic water meter measurements, according to Faraday's law of electromagnetic induction, the induced electromotive force is related to the water flow velocity, magnetic field strength, etc. If the data does not conform to the relationship determined by this law, further verification is required.

[0031] In addition, the communication and data management unit 5 is used to support multiple communication modes, and the user selects a matching communication mode according to the actual usage scenario; The communication and data management unit 5 includes a communication mode selection module 51, a storage and backup module 52 and an automatic data upload module 53; the communication mode selection module 51 is used to set the current usage scenario and automatically match the communication mode according to the usage scenario requirements. When automatically matching the communication mode according to the usage scenario requirements, for areas with weak signals, low-power, long-distance NB-IoT or LoRa communication is selected, and for close-range scenarios with high data transmission rate requirements, Bluetooth or Wi-Fi communication is selected; the storage and backup module 52 is used to store the measurement data in the local database and automatically back up when the communication fails; the automatic data upload module 53 automatically uploads the data to the system's cloud database after the communication is restored to synchronize the system data.

[0032] Meanwhile, the system operation and optimization unit 6 is used to monitor the use of the entire system and optimize the adaptive algorithm according to the system operation data and user needs; The system operation and optimization unit 6 includes a monitoring and diagnosis module 61, a maintenance instruction generation module 62, a data management module 63 and an algorithm optimization module 64; the monitoring and diagnosis module 61 is used to collect various operating data of the water meter system in real time through hardware such as sensors, data acquisition interfaces and supporting monitoring software, and analyze the collected data using fault diagnosis algorithms and expert systems. The fault diagnosis algorithm is based on statistical analysis and machine learning technology to extract features and recognize patterns in the data to determine whether there is a fault in the system and the type and location of the fault. The expert system stores the experience and knowledge of domain experts in the form of rules in a knowledge base, matches and infers the monitoring data through an inference engine, and draws a diagnostic conclusion. When the monitoring and diagnosis module 61 performs diagnosis, when a sensor fault is diagnosed, an instruction to replace the sensor is generated, detailing the sensor model, installation location and replacement steps; if the algorithm parameters need to be adjusted, a corresponding parameter adjustment instruction is generated to specify the parameter name, adjustment range and adjustment method to be adjusted.

[0033] The maintenance instruction generation module 62 automatically generates corresponding maintenance instructions based on the diagnosis results in the monitoring and diagnosis module 61, and sends the instructions to the terminal device of the maintenance personnel; the data management module 63 is used to store, back up, retrieve and analyze the data during the operation of the system; the algorithm optimization module 64 uses machine learning technology to train historical data and adjust the parameters of the algorithm. When the algorithm optimization module 64 optimizes the algorithm, if it is found that the measurement accuracy of the adaptive algorithm decreases under certain complex water flow conditions, the algorithm's parameter update strategy is optimized by learning a large amount of relevant data, so that it can adapt to water flow changes more quickly and accurately, thereby improving measurement accuracy.

[0034] Embodiment 2: A measurement method of a high-precision electromagnetic water meter system based on an adaptive algorithm, comprising the following steps: Step 1: Initialization and parameter setting: After the system is started, the sensor calibration and initialization operations are first performed to set the initial parameters of the adaptive algorithm. According to the installation environment and expected measurement range of the water meter, the initial values ​​of the excitation current, signal amplification factor, filtering parameters, etc. are set. At the same time, the historical data in the storage module is read to provide a reference for the adaptive algorithm. Step 2: Data collection and processing: The sensor collects the induced electromotive force signal generated by the water flow in real time and transmits it to the signal processing and adaptive control unit, which amplifies, filters and performs analog-to-digital conversion on the signal to obtain a digital signal. The adaptive algorithm dynamically adjusts the electrical signal processing parameters according to the electrical signal characteristics, environmental parameters and historical data collected in real time, such as optimizing the amplification factor, updating the filter coefficient, etc., to improve the quality of the digital signal; Step 3: Flow calculation and error correction: The microprocessor calculates the water flow rate using the built-in flow calculation model based on the processed digital signal. During the calculation process, the microprocessor combines the parameters adjusted by the adaptive algorithm and considers the influence of temperature and pressure factors on fluid conductivity and density to perform real-time error correction. For example, by measuring the ambient temperature, the adaptive algorithm automatically adjusts the correlation coefficient in the flow calculation model to compensate for the measurement error caused by temperature changes. In step 3, the built-in traffic calculation model is: Where v is the average flow velocity of water perpendicular to the direction of the magnetic field, r is the inner diameter of the measuring tube, e is the induced electromotive force, q is the magnetic field strength, and L is the flow rate.

[0035] When calculating the water flow, the following contents are also included: 31. Obtaining induced electromotive force: Using sensors to collect induced electromotive force signals generated by water flow in real time, the signal processing and adaptive unit 2 amplifies, filters and performs analog-to-digital conversion on the collected electrical signals to obtain induced electromotive force in the form of stable and accurate digital signals; 32. Determine the magnetic field strength and pipe parameters: The magnetic field strength is determined by the excitation current. During the initialization and parameter setting stage, the appropriate excitation current is set according to the installation environment and expected measurement range of the water meter to determine the magnetic field strength. The inner diameter of the measuring pipe is an inherent parameter of the water meter, which has been determined during design and manufacturing, and the system will store the parameter value. 33. Calculate flow velocity and flow rate: After the microprocessor obtains the induced electromotive force, magnetic field strength and inner diameter parameters of the measuring tube, it calculates the flow velocity of the water flow according to the flow calculation formula, and then obtains the water flow rate; 34. Consider error correction factors: In practical applications, the temperature and pressure factors of the fluid will affect its conductivity and density, and thus affect the measurement results. During the flow calculation process, these factors are considered for real-time error correction in combination with the parameters adjusted by the adaptive algorithm. By measuring the ambient temperature, the adaptive algorithm automatically adjusts the correlation coefficient in the flow calculation model to compensate for the measurement error caused by temperature changes, making the calculated flow closer to the true value.

[0036] Step 4, data storage and transmission: The calculated flow data is stored in the storage module in real time. At the same time, the display and communication module displays the flow data on the display screen, and transmits the data to the remote monitoring center and the abnormal warning unit 4 according to the set communication mode and adaptive communication strategy. The abnormal warning unit 4 determines whether there is abnormal data. If there is no abnormal data, the measurement data of the current system is output. During the data transmission process, the data is encrypted to ensure the security and integrity of the data; Step 5. System monitoring and adaptive adjustment: The system continuously monitors parameters such as sensor status, signal quality, network communication status, and battery power. Once an abnormal situation is found, such as sensor failure, severe signal interference, network interruption, etc., the adaptive algorithm immediately starts the emergency processing procedure and adjusts the system working mode, such as switching to backup sensors, changing the communication method, or reducing system power consumption, to ensure the normal operation of the system. At the same time, based on the monitoring data, the adaptive algorithm continuously optimizes the system parameters to improve measurement accuracy and system stability.

[0037] The method of use and working principle of the device are as follows: first, the electrical signal is collected by the signal acquisition unit 1, and the collected electrical signal is input into the signal processing and adaptive unit 2. After the algorithm matching module 21 matches the algorithm according to the sensor type, the measured fluid characteristics and the environment, the initial parameters are set by the parameter setting and preliminary processing module 22, and the electrical signal is preliminarily processed, so that the collected electrical signal is amplified, filtered and processed by analog-to-digital conversion in turn, and the processed digital signal is transmitted to the dynamic adjustment and continuous processing module 23. The dynamic adjustment and continuous processing module 23 realizes the dynamic adjustment of parameters through cyclic optimization to continuously process the digital signal, and then the flow data transmitted by the signal processing and adaptive unit 2 is processed by the microprocessor chip in the data processing and control unit 3 to calculate the water flow value. According to the system settings and the changes in the measurement environment, the adaptive algorithm is called to adjust the sensor excitation parameters and the signal acquisition frequency to maintain the measurement accuracy. A stable clock signal is provided by the internal clock module to determine the operating frequency of the microprocessor and the synchronous beat of each component.

[0038] The communication mode selection module 51 selects a suitable communication mode, and then the storage and backup module 52 and the automatic data upload module 53 back up and upload the data. According to the set communication mode and adaptive communication strategy, the data is transmitted to the remote monitoring center and the abnormal warning unit 4. The abnormal warning unit 4 monitors and detects the data and the sensor respectively to determine whether there is abnormal data. When there is abnormal data, it is promptly proofread by the abnormal proofreading module 44. If the abnormal data is false information, the warning mechanism of the warning response module 43 is not triggered. When the abnormal data is true information, the warning mechanism of the warning response module 43 is triggered, and the warning response module 43 sends an alarm signal to the control terminal; the operation data of the entire system is monitored by the system operation and optimization unit 6, and the data is feature extracted and pattern recognized to determine whether there is a fault in the system and the type and location of the fault, and the diagnosis is completed. If the water flow data fluctuates abnormally, it is determined whether it is caused by sensor failure, pipeline blockage or other reasons. According to the diagnosis result, the maintenance instruction generation module 62 generates a maintenance instruction, and the staff repairs the system and equipment according to the corresponding maintenance instruction. The data management module 63 manages the large amount of data generated during the operation of the system.

[0039] When managing data, a database is used to store data, which is classified and stored according to data type and time. Data is backed up regularly to prevent data loss. Historical data is mined through data analysis tools to identify the operating rules and potential problems of the system. The algorithm optimization module 64 is used to optimize the adaptive algorithm so that it can adapt to water flow changes more quickly and accurately, thereby improving measurement accuracy.

[0040] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A high-precision electromagnetic water meter system based on an adaptive algorithm, characterized in that: It includes a signal acquisition unit (1), a signal processing and adaptation unit (2), a data processing and control unit (3), an abnormal warning unit (4), a communication and data management unit (5) and a system operation and optimization unit (6); The signal acquisition unit (1) collects the induced electromotive force signal generated by the water flow in real time through the electrode sensor, and transmits the induced electromotive force signal to the signal processing and adaptive unit (2) through a wired connection. The signal processing and adaptive unit (2) amplifies, filters and performs analog-to-digital conversion on the electrical signal to obtain a digital signal, and dynamically adjusts the processing parameters of the digital signal; The signal processing and adaptive unit (2) includes an algorithm matching module (21), a parameter setting and preliminary processing module (22) and a dynamic adjustment and continuous processing module (23), wherein the algorithm matching module (21) is used to select an LMS algorithm or an RLS algorithm according to the sensor type, fluid characteristics and the environment. The parameter setting and preliminary processing module (22) is used to set initial parameters, perform preliminary processing on the collected electrical signals, and complete signal amplification, filtering and analog-to-digital conversion; The dynamic adjustment and continuous processing module (23) continuously monitors the characteristics of the electrical signal and the digital signal through the LMS or RLS algorithm, and calculates and adjusts the parameters in real time; The data processing and control unit (3) completes system control, data processing and execution of the adaptive algorithm through a microprocessor; the abnormal warning unit (4) is used to detect whether there are abnormalities in the sensor status, signal quality and network communication status; the communication and data management unit (5) is used to select a matching communication method according to the actual use scenario; the system operation and optimization unit (6) is used to detect system operation data and user needs and optimize the adaptive algorithm.

2. The high-precision electromagnetic water meter system based on the adaptive algorithm according to claim 1, characterized in that: In the dynamic adjustment and continuous processing module (23), when it is detected that the change in the water flow velocity causes the change in the amplitude of the induced electromotive force signal, the algorithm automatically adjusts the amplification factor or the filtering parameter.

3. The high-precision electromagnetic water meter system based on the adaptive algorithm according to claim 1, characterized in that: The abnormal warning unit (4) comprises a data monitoring module (41), a sensor detection module (42), a warning response module (43) and an abnormality proofreading module (44); The data monitoring module (41) is used to monitor the signal quality and network communication data, and when there is an abnormality in the data, the abnormal data is transmitted to the abnormality correction module (44); The sensor detection module (42) is used to detect the state of the sensor, and if the sensor fails, an abnormal signal is sent to the abnormality correction module (44) in a timely manner; The early warning response module (43) is used to trigger a preset alarm mechanism and send an alarm signal to the control terminal; The abnormality checking module (44) checks the abnormal data, determines the authenticity of the abnormal signal, and transmits the determination result to the early warning response module (43).

4. The high-precision electromagnetic water meter system based on the adaptive algorithm according to claim 3 is characterized by: In the abnormality checking module (44), when checking abnormal data, the following contents are also included: A1. Data feature proofreading: Use statistical methods to calculate the mean and standard deviation of historical data, and then judge abnormal data based on the trend of data changes over time; A2. Sensor performance check: Calibrate the sensor regularly, compare the data before and after calibration, set up multiple redundant sensors to measure the same physical quantity, compare their data, and complete the sensor performance check; A3. Measurement environment assessment: By checking the environmental conditions during measurement and the operating status of the equipment related to the sensor, determine whether the surrounding environment and equipment interfere with the data; A4. Determine the logical relationship of data: Analyze the correlation between abnormal data and other related data, and determine the rationality of the data based on the laws of physics.

5. The high-precision electromagnetic water meter system based on adaptive algorithm according to claim 1, characterized in that: The communication and data management unit (5) comprises a communication mode selection module (51), a storage and backup module (52) and an automatic data upload module (53); The communication mode selection module (51) is used to set the current usage scenario and automatically match the communication mode according to the usage scenario requirements; The storage and backup module (52) is used to store the measurement data in a local database and automatically back up the data when a communication failure occurs; After the communication is restored, the data automatic uploading module (53) automatically uploads the data to the cloud database of the system to synchronize the system data.

6. The high-precision electromagnetic water meter system based on the adaptive algorithm according to claim 5, characterized in that: When the communication mode is automatically matched according to the use scenario requirements in the communication mode selection module (51), for areas with weak signals, low-power, long-distance NB-IoT or LoRa communication is selected, and for scenarios with short distances and high data transmission rate requirements, Bluetooth or Wi-Fi communication is selected.

7. The high-precision electromagnetic water meter system based on adaptive algorithm according to claim 1, characterized in that: The system operation and optimization unit (6) includes a monitoring and diagnosis module (61), a maintenance instruction generation module (62), a data management module (63) and an algorithm optimization module (64). The monitoring and diagnosis module (61) is used to collect various operation data of the water meter system in real time and analyze the collected data using a fault diagnosis algorithm and an expert system. The maintenance instruction generation module (62) automatically generates corresponding maintenance instructions based on the diagnosis results in the monitoring and diagnosis module (61), and sends the instructions to the terminal device of the maintenance personnel; The data management module (63) is used to store, back up, retrieve and analyze data during the operation of the system; The algorithm optimization module (64) uses machine learning technology to train historical data and adjust the parameters of the algorithm.

8. The high-precision electromagnetic water meter system based on the adaptive algorithm according to claim 7, characterized in that: In the monitoring and diagnosis module (61), the fault diagnosis algorithm is based on statistical analysis and machine learning technology to extract features and recognize patterns in the data to determine whether there is a fault in the system and the type and location of the fault. The expert system stores the experience and knowledge of domain experts in the form of rules in the knowledge base, and uses the inference engine to match and infer the monitoring data to draw diagnostic conclusions.

9. A measurement method for a high-precision electromagnetic water meter system based on an adaptive algorithm, characterized in that: A high-precision electromagnetic water meter system based on an adaptive algorithm according to any one of claims 1 to 8 is used, comprising the following steps: S1. Initialization and parameter setting: After the system is started, the sensor calibration and initialization operations are first performed to set the initial parameters of the adaptive algorithm; S2, data acquisition and processing: the sensor acquires the induced electromotive force signal generated by the water flow in real time, and transmits it to the signal processing and adaptive unit (2) to process the electric signal. The adaptive algorithm dynamically adjusts the electric signal processing parameters according to the signal characteristics, environmental parameters and historical data acquired in real time; S3, flow calculation and error correction: the microprocessor calculates the water flow rate using the built-in flow calculation model according to the processed digital signal. During the calculation process, the microprocessor combines the parameters adjusted by the adaptive algorithm and considers the influence of temperature and pressure factors on fluid conductivity and density to perform real-time error correction; S4, data storage and transmission: the calculated flow data is stored in real time, and according to the set communication mode and adaptive communication strategy, the data is transmitted to the remote monitoring center and the abnormal warning unit (4), and the abnormal warning unit (4) determines whether there is abnormal data. If there is no abnormal data, the measurement data of the current system is output; S5. System monitoring and adaptive adjustment: The system continuously monitors the sensor status, signal quality and network communication status. Once an abnormal situation is found, the adaptive algorithm immediately starts the emergency processing procedure and adjusts the system working mode. At the same time, based on the monitoring data, the adaptive algorithm continuously optimizes the system parameters and performs adaptive adjustments.

10. The measuring method of the high-precision electromagnetic water meter system based on the adaptive algorithm according to claim 9, characterized in that: In S3, the built-in traffic calculation model is: In the formula, v is the average velocity of the water flow perpendicular to the magnetic field, r is the inner diameter of the measuring tube, e is the induced electromotive force, q is the magnetic field intensity, and L is the flow rate; When calculating the water flow, the following contents are also included: S31, obtaining induced electromotive force: using the sensor to collect the induced electromotive force signal generated by the water flow in real time, the signal processing and adaptive unit (2) amplifies, filters and performs analog-to-digital conversion on the collected electrical signal to obtain the induced electromotive force in the form of a stable and accurate digital signal; S32, determining magnetic field strength and pipe parameters: in the initialization and parameter setting stage, according to the installation environment and expected measurement range of the water meter, set a suitable excitation current to determine the magnetic field strength, wherein the inner diameter of the measuring pipe is an inherent parameter of the water meter; S33, calculating flow velocity and flow rate: after the processor in the data processing and control unit (3) obtains the induced electromotive force, magnetic field strength and inner diameter parameters of the measuring tube, it calculates the flow velocity of the water flow according to the flow calculation formula, and then obtains the water flow rate; S34. Considering error correction factors: In the process of flow calculation, in combination with the parameters adjusted by the adaptive algorithm, the temperature and pressure factors of the fluid are considered to perform real-time error correction to compensate for the measurement error caused by temperature changes.

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