Iot-based ultrasonic water meter fault monitoring and early warning method and system

Abstract

The application discloses an ultrasonic water meter fault monitoring and early warning method and system based on the Internet of Things, relates to the technical field of ultrasonic water meter monitoring, and comprises multiple modules to realize fault monitoring and early warning of the ultrasonic water meter; first, the water quality state information and the ultrasonic signal attenuation condition of each period are monitored, and after feature extraction and analysis, the water quality index evaluation level and the ultrasonic signal attenuation condition in the corresponding monitoring period are acquired and are subjected to correlation analysis, so that the influence degree of the water quality index on signal attenuation in the ultrasonic transmission process is analyzed, and it is judged whether a preliminary early warning instruction is sent; after receiving the preliminary early warning, the dirt coverage state information and the in-pipe blockage state information of the monitoring components are monitored, are subjected to dimensionless processing, and are subjected to evaluation of the fault state of the water meter through a machine learning model; after comparative analysis, the corresponding fault monitoring and early warning instruction is obtained and is executed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ultrasonic water meter monitoring, in particular to an ultrasonic water meter fault monitoring and early warning method and system based on the Internet of Things. BACKGROUND

[0002] In modern water resource management, ultrasonic water meters have become the mainstream equipment for water flow measurement due to their high precision, low maintenance and long service life. Such water meters measure water flow rate through ultrasonic technology, providing accurate flow data and showing their reliability in a wide range of applications. However, as the use time extends and environmental conditions change, ultrasonic water meters face various potential faults, including signal attenuation, component contamination and pipe blockage. These faults not only affect the measurement accuracy of the water meter, but also cause errors in water resource management, thereby affecting water management and user water experience. Therefore, fault monitoring and early warning for ultrasonic water meters is an important task to ensure normal operation and maintenance management of the equipment.

[0003] Although existing ultrasonic water meter fault monitoring and early warning measures have made some progress in detecting equipment abnormalities, there are still some deficiencies in actual application, especially the influence of water quality changes on the measurement accuracy of the water meter is often ignored. Changes in suspended solids and turbidity in water quality can cause attenuation of ultrasonic signals, and long-term deposition can also cause blockage problems, thereby affecting the measurement of water flow by ultrasonic water meters. This influence can cause inaccurate data measurement by ultrasonic water meters. Therefore, developing an ultrasonic water meter fault monitoring and early warning method and system based on the Internet of Things is of great significance to improve the fault monitoring capability of ultrasonic water meters and optimize the response efficiency of early warning. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides an ultrasonic water meter fault monitoring and early warning method and system based on the Internet of Things, which solves the problems in the background art.

[0005] To achieve the above purpose, the present application realizes the following technical scheme: an ultrasonic water meter fault monitoring and early warning system based on the Internet of Things, comprising a first monitoring module, a pre-analysis module, a correlation analysis module, a second monitoring module, a water meter fault comprehensive evaluation module and a fault early warning module;

[0006] The first monitoring module is used for real-time monitoring of water quality state information and ultrasonic signal attenuation in each period of the ultrasonic water meter, and after feature extraction, water quality state information dataset and ultrasonic signal propagation state dataset are obtained respectively;

[0007] The pre-analysis module is configured to analyze the water quality state information dataset and the ultrasonic signal propagation state dataset to obtain a water quality index evaluation level and an ultrasonic signal attenuation condition in a corresponding monitoring period;

[0008] The correlation analysis module is configured to correlate the water quality index evaluation level and the ultrasonic signal attenuation condition in the corresponding monitoring period to analyze an influence degree of the water quality index on signal attenuation in the ultrasonic transmission process and determine whether to issue a preliminary warning instruction;

[0009] The second monitoring module is configured to monitor, after receiving the preliminary warning instruction, a component dirt coverage state information and a pipe blockage state information in the ultrasonic water meter by a plurality of groups of sensors to obtain a component dirt coverage state information dataset and a pipe blockage state information dataset, respectively.

[0010] The water meter fault comprehensive evaluation module is configured to correlate the component dirt coverage state information dataset and the pipe blockage state information dataset to evaluate a fault state of the water meter.

[0011] The fault warning module is configured to compare and analyze the fault state of the water meter to obtain a corresponding fault monitoring and warning instruction and execute the same.

[0012] Preferably, the first monitoring module is configured to monitor, in real time, a water quality state and an ultrasonic signal attenuation condition in each period of the ultrasonic water meter, and after feature extraction, obtain a water quality state information dataset and an ultrasonic signal propagation state dataset, specifically as follows.

[0013] The first monitoring module includes a water quality monitoring unit and a signal attenuation monitoring unit.

[0014] The water quality monitoring unit is configured to monitor, in real time, a water quality state in each period of the ultrasonic water meter, and after water quality feature extraction, obtain a water quality state information dataset.

[0015] The water quality feature extraction is performed by identifying and extracting the water quality state information dataset monitored in real time to extract key indicators, including water hardness, suspended solid content, and turbidity.

[0016] The signal attenuation monitoring unit is configured to monitor, in real time, an ultrasonic signal attenuation condition in each period, and after signal feature extraction, obtain an ultrasonic signal propagation state dataset.

[0017] The signal feature extraction is performed by identifying and extracting the ultrasonic signal propagation state dataset monitored in real time to extract key indicators, including a downstream receiving signal intensity and an upstream receiving signal intensity.

[0018] Preferably, the pre-analysis module is configured to analyze the water quality state information dataset and the ultrasonic signal propagation state dataset to obtain water quality index evaluation levels and ultrasonic signal attenuation conditions in a corresponding monitoring period, and specifically configured to:

[0019] The pre-analysis module comprises a water quality state pre-analysis unit and a signal attenuation pre-analysis unit.

[0020] The water quality state pre-analysis unit is configured to analyze the water quality state information dataset, perform dimensionless processing, and obtain water quality index evaluation levels in a corresponding monitoring period based on key indicators of water quality state and set weights.

[0021] The signal attenuation pre-analysis unit is configured to analyze the ultrasonic signal propagation state dataset, perform dimensionless processing, and obtain ultrasonic signal attenuation conditions in a corresponding monitoring period based on key indicators of ultrasonic signal and set weights.

[0022] The dimensionless processing is to normalize parameters with different units in the water quality state information dataset and the ultrasonic signal propagation state dataset into pure numerical values without units.

[0023] Preferably, the correlation analysis module is configured to associate water quality index evaluation levels and ultrasonic signal attenuation conditions in a corresponding monitoring period to analyze the influence degree of water quality indexes on signal attenuation in the ultrasonic transmission process and determine whether to issue a preliminary warning instruction, and specifically configured to:

[0024] The correlation analysis module comprises an attenuation correlation analysis unit and a determination unit.

[0025] The attenuation correlation analysis unit is configured to associate water quality index evaluation levels and ultrasonic signal attenuation conditions in a corresponding monitoring period, perform dimensionless processing based on a statistical algorithm of data distribution characteristics, and analyze the influence degree of water quality indexes on signal attenuation in the ultrasonic transmission process.

[0026] The determination unit is configured to determine whether to issue a preliminary warning instruction according to the influence degree of water quality indexes on signal attenuation in the ultrasonic transmission process after comparison, and the specific content is as follows:

[0027] If the water quality indexes have an influence on signal attenuation in the ultrasonic transmission process, a preliminary warning instruction is issued, and the influence of water quality is further analyzed; otherwise, no additional preliminary warning instruction is issued.

[0028] Preferably, the second monitoring module is configured to monitor the component fouling coverage state information and the pipe blockage state information in the ultrasonic water meter through a plurality of groups of sensors after receiving the preliminary warning instruction, and obtain a component fouling coverage state information dataset and a pipe blockage state information dataset, specifically as follows:

[0029] After receiving the preliminary warning instruction, the component fouling coverage state information in the ultrasonic water meter is monitored by the camera sensor and the ultrasonic thickness measurement sensor to obtain a component fouling coverage state information dataset.

[0030] The pipe blockage state information is monitored by the volumetric flow sensor and the ultrasonic thickness measurement sensor to obtain a pipe blockage state information dataset.

[0031] Preferably, the water meter fault comprehensive evaluation module is configured to associate the component fouling coverage state information dataset and the pipe blockage state information dataset, and evaluate the fault state of the water meter, and the specific evaluation process is as follows:

[0032] The water meter fault comprehensive evaluation module includes a fouling coverage analysis unit, a pipe blockage analysis unit, and a water meter fault evaluation unit.

[0033] Based on the obtained component fouling coverage state information dataset, the key factors of fouling coverage are weighted.

[0034] The fouling coverage analysis unit generates a calculation formula based on the obtained component fouling coverage state information dataset and the set weight after dimensionless processing, to analyze the component fouling coverage.

[0035] Preferably, the pipe blockage analysis unit sets weights for the key factors of pipe blockage based on the obtained pipe blockage state information dataset.

[0036] Based on the obtained pipe blockage state information dataset and the set weight, a calculation formula is generated after dimensionless processing to analyze the pipe blockage.

[0037] Preferably, the water meter fault evaluation unit sets weights based on the influence degree of the obtained fouling coverage and pipe blockage on the fault state of the water meter.

[0038] The analyzed fouling coverage and pipe blockage are associated, and a calculation formula is generated after dimensionless processing combined with the set weight to evaluate the fault state of the water meter.

[0039] Preferably, the fault warning module is configured to compare and analyze the fault state of the water meter to obtain corresponding fault monitoring warning instructions and execute them, and the specific process is as follows:

[0040] The fault early warning module comprises a comparison unit and an early warning unit;

[0041] The comparison unit is used for comparative analysis of the fault state of the water meter to obtain corresponding fault monitoring and early warning instructions, and the specific content of the fault monitoring and early warning instructions is as follows:

[0042] If the water meter is in a fault state, it indicates that the current ultrasonic water meter function state is abnormal and has a risk of failure, and at this time, a first fault monitoring and early warning instruction is issued;

[0043] If the water meter is not in a fault state, it indicates that the current ultrasonic water meter function state is not abnormal and has no risk of failure, and at this time, a second fault monitoring and early warning instruction is issued;

[0044] The early warning unit is used for receiving the first fault monitoring and early warning instruction and the second fault monitoring and early warning instruction, and specifically performing the following content;

[0045] When the first environmental monitoring and early warning instruction is received, the content of execution is to enable the backup water meter, the system automatically switches the water supply pipeline to the standby equipment to ensure the normal supply of water flow; automatically sends an alarm notice to the maintenance personnel, informs the existing fault risk and specific abnormal situation through the way of short message and email, generates a fault report and sends it to the maintenance personnel, the fault report contains water meter fault evaluation information, specific component dirt coverage state information and pipe blockage state information, and related water quality and ultrasonic signal attenuation data information for subsequent maintenance and fault analysis; activate the audible and visual alarm device to remind nearby personnel;

[0046] When the second environmental monitoring and early warning instruction is received, the content of execution is to record the current monitoring data in the system database as log information of the normal operation of the system for later trend analysis and system debugging, continue to collect and analyze data according to the established monitoring period, do not need to take additional measures, and do not trigger any alarm and notification.

[0047] Preferably, the ultrasonic water meter fault monitoring and early warning method based on the Internet of Things comprises the following steps:

[0048] Step 1, real-time monitoring of the water quality state information and ultrasonic signal attenuation of each period in the ultrasonic water meter, and after feature extraction, obtaining a water quality state information dataset and an ultrasonic signal propagation state dataset respectively;

[0049] Step 2, analyzing the water quality state information dataset and the ultrasonic signal propagation state dataset, associating the water quality index evaluation level and the ultrasonic signal attenuation in the corresponding monitoring period to analyze the influence degree of the water quality index on the signal attenuation in the ultrasonic transmission process, and determining whether to issue a preliminary early warning instruction;

[0050] Step three, after receiving the preliminary warning instruction, the state information of the component dirt coverage and the pipe blockage in the ultrasonic water meter are monitored by several groups of sensors, the obtained component dirt coverage state information dataset and the pipe blockage state information dataset are associated, and the fault state of the water meter is evaluated;

[0051] Step four, the fault state of the water meter is compared and analyzed to obtain the corresponding fault monitoring and warning instruction and execute. The present application provides an ultrasonic water meter fault monitoring and warning method and system based on Internet of Things, which has the following beneficial effects:

[0052] (1) The first monitoring module collects water quality state information and ultrasonic signal attenuation in real time based on Internet of Things sensors, providing key data for subsequent analysis. The pre-analysis module deeply analyzes the data to generate water quality index evaluation value Zsz and ultrasonic signal attenuation coefficient Zsj, so that the influence of water quality change on signal transmission is accurately quantified. The correlation analysis module further associates water quality index evaluation value Zsz and ultrasonic signal attenuation coefficient Zsj to analyze the influence degree of water quality index on signal attenuation in the ultrasonic transmission process, generates attenuation correlation index Zgs, and compares it with the preset correlation threshold L to timely issue a preliminary warning instruction for further analysis. The second monitoring module monitors the component dirt coverage and pipe blockage state inside the water meter using multiple groups of sensors based on Internet of Things after receiving the preliminary warning instruction, obtains the relevant data set, and the water meter fault comprehensive evaluation module analyzes the influence of component dirt and pipe blockage through dimensionless processing and machine learning model, and fits the water meter fault evaluation index Zgz. Finally, the fault warning module compares the water meter fault evaluation index Zgz with the set fault evaluation threshold G, generates the corresponding fault monitoring and warning instruction and executes. In summary, this system can effectively monitor and warn that the changes in suspended solids and turbidity in water will cause the attenuation of ultrasonic signals, and long-term deposition will also cause blockage leading to inaccurate measurement data of ultrasonic water meter, improving the fault monitoring capability and optimizing the warning response efficiency of ultrasonic water meter.

[0053] (2) The water quality state information dataset and ultrasonic signal propagation state dataset are analyzed, the water quality index evaluation value Zsz and ultrasonic signal attenuation coefficient Zsj obtained in the corresponding monitoring period are analyzed, the attenuation correlation index Zgs is generated, and the attenuation correlation index Zgs is compared with the pre-set correlation threshold L to accurately determine whether the water quality index has an impact on the ultrasonic transmission state, and then decide whether to issue a preliminary warning instruction. This analysis process can timely and accurately identify the influence degree of water quality index on signal attenuation in the ultrasonic transmission process, improving the reliability of monitoring and warning during the operation of the water meter.

[0054] (3) Through in-depth analysis of the dirt coverage of components and the state of pipe blockage, a water meter fault evaluation index Zgz is generated, by evaluating the influence of dirt coverage and pipe blockage, various fault factors can be comprehensively considered, and comprehensive fault evaluation results are provided, after the water meter fault evaluation index Zgz is compared with the preset fault evaluation threshold G, the early warning instruction can be accurately sent, the backup device is switched in time, the maintenance personnel are notified and the alarm device is activated, this multi-level and multi-faceted fault evaluation and early warning mechanism ensures the stability and accuracy of the water meter, and reduces the water metering error caused by water meter failure. BRIEF DESCRIPTION OF DRAWINGS

[0055] Figure 1 The figure is a block diagram of the ultrasonic water meter fault monitoring and early warning system based on the Internet of Things.

[0056] Figure 2 The figure is a flowchart of the ultrasonic water meter fault monitoring and early warning method based on the Internet of Things. DETAILED DESCRIPTION

[0057] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0058] Embodiment 1

[0059] Please refer to Figure 1 The present application provides an ultrasonic water meter fault monitoring and early warning system based on the Internet of Things, which comprises a first monitoring module, a pre-analysis module, a correlation analysis module, a second monitoring module, a water meter fault comprehensive evaluation module and a fault warning module.

[0060] The first monitoring module is used for real-time monitoring of water quality state information and ultrasonic signal attenuation of each period in the ultrasonic water meter, and after feature extraction, water quality state information dataset and ultrasonic signal propagation state dataset are obtained respectively.

[0061] The pre-analysis module is used for analyzing the water quality state information dataset and the ultrasonic signal propagation state dataset, and obtaining the water quality index evaluation value Zsz and the ultrasonic signal attenuation coefficient Zsj in the corresponding monitoring period respectively.

[0062] The correlation analysis module is configured to correlate the water quality index evaluation value Zsz and the ultrasonic signal attenuation coefficient Zsj in the corresponding monitoring period, analyze the influence degree of the water quality index on the signal attenuation in the ultrasonic transmission process, generate an attenuation correlation index Zgs, and compare the attenuation correlation index Zgs with a pre-set correlation threshold L to determine whether to issue a preliminary warning instruction.

[0063] The second monitoring module is configured to monitor the dirt coverage state information of the components in the ultrasonic water meter and the pipe blockage state information after receiving the preliminary warning instruction, and obtain a component dirt coverage state information dataset and a pipe blockage state information dataset, respectively.

[0064] The water meter fault comprehensive evaluation module is configured to perform dimensionless processing on the component dirt coverage state information dataset and the pipe blockage state information dataset, and use a machine learning model to fit a water meter fault evaluation index Zgz.

[0065] The fault warning module is configured to compare the water meter fault evaluation index Zgz with a pre-set fault evaluation threshold G, obtain a corresponding fault monitoring warning instruction, and execute the fault monitoring warning instruction.

[0066] In this embodiment, the ultrasonic water meter fault monitoring and warning system based on the Internet of Things collects water quality state information and ultrasonic signal attenuation in real time based on Internet of Things sensors, provides key data for subsequent analysis, the pre-analysis module performs in-depth analysis on the data, generates a water quality index evaluation value Zsz and an ultrasonic signal attenuation coefficient Zsj, accurately quantifies the influence of water quality changes on signal transmission, the correlation analysis module further correlates the water quality index evaluation value Zsz and the ultrasonic signal attenuation coefficient Zsj to analyze the influence degree of the water quality index on the signal attenuation in the ultrasonic transmission process, generates an attenuation correlation index Zgs, and compares the attenuation correlation index Zgs with a pre-set correlation threshold L to timely issue a preliminary warning instruction for further analysis. After receiving the preliminary warning instruction, the second monitoring module uses multiple groups of sensors based on the Internet of Things to monitor the dirt coverage of components and the pipe blockage state in the water meter, obtains relevant datasets, the water meter fault comprehensive evaluation module analyzes the influence of component dirt and pipe blockage by dimensionless processing and a machine learning model, and fits a water meter fault evaluation index Zgz. Finally, the fault warning module compares the water meter fault evaluation index Zgz with a pre-set fault evaluation threshold G, generates a corresponding fault monitoring warning instruction, and executes the fault monitoring warning instruction. In summary, the system can effectively monitor and warn that changes in suspended solids and turbidity in water will cause attenuation of ultrasonic signals, and long-term deposition will also cause blockage problems, leading to inaccurate measurement data of ultrasonic water meters, and improve the accuracy and pertinence of ultrasonic water meter fault monitoring.

[0067] Embodiment 2

[0068] Please refer to Figure 1 , specifically: the first monitoring module includes a water quality monitoring unit and a signal attenuation monitoring unit;

[0069] The water quality monitoring unit is used to monitor the water quality state information of each period in the ultrasonic water meter in real time through a water hardness sensor, a sediment analyzer and a turbidity sensor, and to obtain a water quality state information dataset after feature extraction, the water quality state information dataset including water hardness Dsy, suspended solid content Khk and turbidity Dhz of each monitoring period;

[0070] The signal attenuation monitoring unit is used to monitor the ultrasonic signal attenuation of each period in real time through an acoustic sensor, and to obtain an ultrasonic signal propagation state dataset after feature extraction, the ultrasonic signal propagation state dataset including downstream receiving signal intensity Qsx and upstream receiving signal intensity Qnx of each monitoring period, it should be noted that the downstream receiving signal intensity Qsx refers to the signal intensity received by the receiver after the ultrasonic signal transmitted a specified distance along the water flow direction in the ultrasonic water meter, the signal transmission direction is consistent with the water flow direction; the upstream receiving signal intensity Qnx refers to the signal intensity received by the receiver after the ultrasonic signal transmitted a specified distance against the water flow direction in the ultrasonic water meter, the signal transmission direction is opposite to the water flow direction.

[0071] In this embodiment, by integrating the water quality monitoring unit and the signal attenuation monitoring unit, comprehensive monitoring of the internal water quality and signal propagation state of the ultrasonic water meter is realized, thereby significantly improving the fault early warning capability of the system, the water quality monitoring unit uses a water hardness sensor, a sediment analyzer and a turbidity sensor to accurately obtain water quality state information, including water hardness Dsy, suspended solid content Khk and turbidity Dhz, these parameters are crucial for evaluating the influence of water quality changes on ultrasonic signal transmission, through real-time monitoring and feature extraction, the system can timely identify the potential influence of water quality on ultrasonic signal attenuation, the signal attenuation monitoring unit accurately captures the downstream and upstream ultrasonic signal intensity through an acoustic sensor, thereby identifying the signal attenuation caused by water quality problems, and providing accurate data support for fault early warning.

[0072] Embodiment 3

[0073] Please refer to Figure 1 , specifically: the pre-analysis module includes a water quality state pre-analysis unit and a signal attenuation pre-analysis unit;

[0074] The water quality state pre-analysis unit is configured to analyze the water quality state information dataset, and after non-dimensional processing, a water quality index evaluation value Zsz in a corresponding monitoring period is obtained by fitting, specifically by the following formula:

[0075]

[0076] In the formula, Dsy represents water hardness, Khk represents suspended solid content, Dhz represents turbidity, and α1, α2 and α3 all represent weight values;

[0077] Specifically, the signal attenuation pre-analysis unit is configured to analyze the ultrasonic wave signal propagation state dataset, and after non-dimensional processing, an ultrasonic wave signal attenuation coefficient Zsj in a corresponding monitoring period is obtained by fitting, specifically by the following formula:

[0078]

[0079] In the formula, Qsx represents a forward water received signal intensity, Qnx represents a reverse water received signal intensity, and Qbz represents a transmitter transmitted signal intensity. The logarithmic function reflects the non-linear effect of signal attenuation.

[0080] Specifically, the correlation analysis module includes an attenuation correlation analysis unit and a determination unit.

[0081] The attenuation correlation analysis unit is configured to correlate the water quality index evaluation value Zsz and the ultrasonic wave signal attenuation coefficient Zsj in a corresponding monitoring period, to analyze the influence degree of the water quality index on signal attenuation in the ultrasonic wave transmission process, to generate an attenuation correlation index Zgs, specifically by the following formula:

[0082]

[0083] In the formula, Cov(Zsz, Zsj) represents the covariance between the water quality index evaluation value Zsz and the ultrasonic wave signal attenuation coefficient Zsj, and σZsz and σZsj represent the standard deviation of the water quality index evaluation value Zsz and the standard deviation of the ultrasonic wave signal attenuation coefficient Zsj; by using the formula of covariance and standard deviation, the attenuation correlation index Zgs can be intuitively understood as the ratio of the covariance between the water quality index evaluation value Zsz and the ultrasonic wave signal attenuation coefficient Zsj to the respective standard deviations, thereby describing the degree of linear correlation between the two.

[0084] The determination unit is configured to pre-set a correlation threshold L, and compare the correlation threshold L with the attenuation correlation index Zgs to determine whether the water quality index has an influence on the ultrasonic wave transmission state, specifically as follows:

[0085] If the attenuation correlation index Zgs is greater than the correlation threshold L, it indicates that the current water quality index has an impact on the ultrasonic transmission state, and a preliminary warning instruction is issued. At this time, the water quality impact situation will be further analyzed.

[0086] If the attenuation correlation index Zgs is less than the correlation threshold L, it indicates that the current water quality index has an impact on the ultrasonic transmission state, and a preliminary warning instruction is issued. At this time, the water quality impact situation will be further analyzed.

[0087] If the attenuation correlation index Zgs is equal to the correlation threshold L, it indicates that the current water quality index has no impact on the ultrasonic transmission state at the moment, and no additional preliminary warning instruction is issued.

[0088] In this embodiment, the pre-analysis module improves the intelligence and accuracy of ultrasonic water meter fault monitoring by accurately analyzing water quality state information and ultrasonic signal propagation state data. The water quality state pre-analysis unit uses dimensionless processing technology to comprehensively evaluate the water quality state information and generate a water quality index evaluation value Zsz. Through weight value adjustment, it accurately reflects the comprehensive influence of water hardness Dsy, suspended solid content Khk and turbidity Dhz on water quality. The signal attenuation pre-analysis unit calculates the ultrasonic signal attenuation coefficient Zsj by analyzing the ultrasonic signal propagation state data, which can effectively capture nonlinear signal attenuation effects and provide data support for further analysis. The correlation analysis module performs correlation analysis on the water quality index evaluation value Zsz and the ultrasonic signal attenuation coefficient Zsj through the attenuation correlation analysis unit to generate an attenuation correlation index Zgs. The influence degree of water quality index on ultrasonic signal attenuation is described by the ratio of covariance and standard deviation. The determination unit compares the attenuation correlation index Zgs with the pre-set correlation threshold L to accurately determine whether the water quality index has an impact on the ultrasonic transmission state, and then decides whether to issue a preliminary warning instruction. This systematic analysis process can timely and accurately identify and warn the potential impact of water quality on ultrasonic water meters, improve the operation reliability and maintenance efficiency of water meters, and reduce the risk of failure.

[0089] Embodiment 4

[0090] Please refer to Figure 1Specifically, the second monitoring module is configured to receive the preliminary early warning instruction, monitor the dirt coverage state information of the components in the ultrasonic water meter through the camera sensor and the ultrasonic thickness measurement sensor, and obtain a component dirt coverage state information dataset, which includes a component dirt coverage area Mzb and a component dirt coverage average thickness Hyq; the second monitoring module is also configured to monitor the pipe blockage state information through the positive displacement flow sensor and the ultrasonic thickness measurement sensor, and obtain a pipe blockage state information dataset, which includes a pipe deposit volume Vcj and a pipe wall dirt coverage average thickness Hgb.

[0091] It should be noted that the component dirt coverage will cause the attenuation of the transmission and reception signal strength of the ultrasonic water meter, thereby affecting the measurement accuracy of the ultrasonic water meter; and the pipe blockage will cause the actual passing area of the water flow in the pipe to be smaller than the cross section of the pipe, so that the water flow velocity measured by the ultrasonic water meter is larger, thereby causing the actual measurement value of the water flow to be larger.

[0092] In this embodiment, the camera sensor and the ultrasonic thickness measurement sensor are used to monitor the component dirt coverage state inside the ultrasonic water meter in detail, so that the component dirt coverage state information dataset, including the component dirt coverage area Mzb and the component dirt coverage average thickness Hyq, can be obtained in real time. These data provide a key basis for evaluating the working state of the ultrasonic water meter. The dirt coverage will cause the attenuation of the transmission and reception signal strength, affecting the measurement accuracy of the water meter, thereby causing inaccurate flow measurement. In addition, the second monitoring module also monitors the pipe blockage state through the positive displacement flow sensor and the ultrasonic thickness measurement sensor, and obtains the pipe deposit volume Vcj and the pipe wall dirt coverage average thickness Hgb data. The pipe blockage will reduce the actual passing area of the water flow, so that the water flow velocity measured by the ultrasonic water meter is larger, thereby causing the actual measurement value to be higher. Through the comprehensive understanding of the internal situation of the ultrasonic water meter, potential problems caused by component dirt and pipe blockage can be identified in a timely manner.

[0093] Embodiment 5

[0094] Please refer to Figure 1 Specifically, the water meter fault comprehensive evaluation module includes a dirt coverage analysis unit, a pipe blockage analysis unit, and a water meter fault evaluation unit.

[0095] The dirt coverage analysis unit is configured to analyze the component dirt coverage state information dataset. After dimensionless processing, the dirt coverage index Zfg is fitted and obtained. The dirt coverage index Zfg is obtained by the following formula:

[0096]

[0097] In the formula, Mzb represents the component device dirt coverage area, Hyq represents the component device dirt coverage average thickness, δ1 and δ2 respectively represent the weight values of the component device dirt coverage area Mzb and the component device dirt coverage average thickness Hyq, and A represents the first correction constant.

[0098] Specifically, the pipe internal blockage analysis unit is configured to analyze the pipe internal blockage state information dataset, and after dimensionless processing, the pipe internal blockage index Zzs is obtained by fitting. The pipe internal blockage index Zzs is obtained by the following formula:

[0099]

[0100] In the formula, Vcj represents the volume of the pipe internal deposit, Hgb represents the average thickness of the pipe wall dirt coverage, γ1 and γ2 both represent the weight values, and B represents the second correction constant.

[0101] Specifically, the water meter fault evaluation unit is configured to associate the dirt coverage index Zfg with the pipe internal blockage index Zzs to obtain a water meter fault evaluation index Zgz. The water meter fault evaluation index Zgz is obtained by the following formula:

[0102] Zgz=μ1×Zfg+μ2×Zzs+C;

[0103] In the formula, Zfg represents the dirt coverage index, Zzs represents the pipe internal blockage index, μ1 and μ2 respectively represent the weight values of the dirt coverage index Zfg and the pipe internal blockage index Zzs, and C represents the third correction constant.

[0104] In this embodiment, through the cooperation of the dirt coverage analysis unit, the pipe blockage analysis unit and the water meter fault evaluation unit, the comprehensive evaluation ability of the ultrasonic water meter state is improved. The dirt coverage analysis unit obtains the dirt coverage index Zfg by dimensionless processing of the component dirt coverage state information dataset, which considers the component dirt coverage area Mzb and the component dirt coverage average thickness Hyq, and optimizes the result through the set weight value and the correction constant. This analysis can effectively evaluate the influence of dirt on ultrasonic signal attenuation. The pipe blockage analysis unit focuses on the pipe sediment volume Vcj and the pipe wall dirt coverage average thickness Hgb, and calculates the pipe blockage index Zzs through dimensionless processing, which reflects the influence of pipe blockage on water flow through and the measurement error of the water meter to water flow. The water meter fault evaluation unit integrates the dirt coverage index Zfg and the pipe blockage index Zzs, and calculates the water meter fault evaluation index Zgz through the set weight value and the correction constant to comprehensively evaluate the running state of the ultrasonic water meter. This evaluation method not only can identify and quantify the water meter fault risk, but also can provide data support for preventive maintenance, so as to improve the measurement accuracy of the water meter and the overall reliability of the system.

[0105] Embodiment 6

[0106] Please refer to Figure 1 , specifically: the fault warning module includes a comparison unit and a warning unit;

[0107] The comparison unit is used to pre-set a fault evaluation threshold G, and compare the water meter fault evaluation index Zgz with the pre-set fault evaluation threshold G to obtain a corresponding fault monitoring warning instruction. The specific content of the fault monitoring warning instruction is as follows:

[0108] If the water meter fault evaluation index Zgz is greater than or equal to the fault evaluation threshold G, that is, Zgz≥G, a first fault monitoring warning instruction is obtained, indicating that there is an abnormality in the current ultrasonic water meter function state and there is a risk of failure. At this time, the first fault monitoring warning instruction is issued;

[0109] If the water meter fault evaluation index Zgz is less than the fault evaluation threshold G, that is, Zgz<G, a second fault monitoring warning instruction is obtained, indicating that there is no abnormality in the current ultrasonic water meter function state and there is no risk of failure. At this time, the second fault monitoring warning instruction is issued;

[0110] The warning unit is used to receive the first fault monitoring warning instruction and the second fault monitoring warning instruction, and specifically execute the following contents;

[0111] When receiving the first environmental monitoring warning instruction, the execution content is to enable the backup water meter, the system automatically switches the water supply pipeline to the backup device to ensure the normal supply of water flow; automatically sends an alarm notification to the maintenance personnel, informs the existing fault risk and specific abnormal situation through the way of short message and email, and generates a fault report which is sent to the maintenance personnel, the fault report contains water meter fault evaluation information, specific component dirt coverage state information and pipe blockage state information, and related water quality and ultrasonic signal attenuation data information for subsequent maintenance and fault analysis; activate the audible and visual alarm device to remind nearby personnel to pay attention;

[0112] When receiving the second environmental monitoring warning instruction, the execution content is to record the current monitoring data in the system database as log information of the normal operation of the system for subsequent trend analysis and system debugging, continue to collect and analyze data according to the established monitoring period, without taking additional measures, and without triggering any alarm and notification.

[0113] In this embodiment, the comparison unit and the warning unit improve the fault monitoring and warning capability of the ultrasonic water meter. The comparison unit compares the water meter fault evaluation index Zgz with the pre-set fault evaluation threshold G to determine whether the state of the ultrasonic water meter is abnormal. If the water meter fault evaluation index Zgz is greater than or equal to the fault evaluation threshold G, the system will issue a first fault monitoring warning instruction, indicating that the water meter has a fault risk. At this time, the warning unit will automatically enable the backup water meter to ensure the continuous supply of water flow, and notify the maintenance personnel through short message and email to provide detailed fault information and fault report to help quickly locate and repair the problem. At the same time, the audible and visual alarm device is activated to remind nearby personnel to improve vigilance. If the water meter fault evaluation index Zgz is less than the fault evaluation threshold G, the system will issue a second fault monitoring warning instruction, indicating that the current state is normal. The system will record the monitoring data as log information for subsequent analysis and system debugging, and continue to monitor according to the established period without additional intervention. Such design not only effectively guarantees the continuous and stable operation of the water meter, but also timely responds to potential fault risks, optimizes the maintenance process, and enhances the reliability and safety of the system.

[0114] Embodiment 7

[0115] Please refer to Figure 1 and Figure 2 , specifically: the ultrasonic water meter fault monitoring and warning method based on the Internet of Things, comprising the following steps:

[0116] Step one, real-time monitoring of the water quality state information and ultrasonic signal attenuation of each period in the ultrasonic water meter, and after feature extraction, obtaining water quality state information dataset and ultrasonic signal propagation state dataset respectively;

[0117] Step two, analyzing the water quality state information data set and the ultrasonic signal propagation state data set, associating the water quality index evaluation level and the ultrasonic signal attenuation condition in the corresponding monitoring period to analyze the influence degree of the water quality index on the signal attenuation in the ultrasonic transmission process, and determining whether to issue a preliminary warning instruction;

[0118] Step three, after receiving the preliminary warning instruction, monitoring the component dirt coverage state information and the pipe blockage state information in the ultrasonic water meter by a plurality of groups of sensors, associating the obtained component dirt coverage state information data set and pipe blockage state information data set, and evaluating the fault state of the water meter;

[0119] Step four, comparing and analyzing the fault state of the water meter to obtain a corresponding fault monitoring and warning instruction and execute it.

[0120] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. The ultrasonic water meter fault monitoring and early warning system based on the Internet of Things is characterized by: It includes a first monitoring module, a pre-analysis module, a correlation analysis module, a second monitoring module, a water meter fault comprehensive evaluation module and a fault warning module; the first monitoring module is used to monitor the water quality status information and ultrasonic signal attenuation of each time period in the ultrasonic water meter in real time, and obtain a water quality status information data set and an ultrasonic signal propagation status data set after feature extraction; the pre-analysis module is used to analyze the water quality status information data set and the ultrasonic signal propagation status data set to obtain the water quality index evaluation level and ultrasonic signal attenuation in the corresponding monitoring period; the correlation analysis module is used to correlate the water quality index evaluation level and ultrasonic signal attenuation in the corresponding monitoring period, The method is used to analyze the degree of influence of water quality indicators on signal attenuation during ultrasonic transmission to determine whether to issue a preliminary warning instruction; the second monitoring module is used to monitor the dirt coverage status information of components and the blockage status information of pipes in the ultrasonic water meter through a plurality of groups of sensors after receiving the preliminary warning instruction, and obtain a component dirt coverage status information data set and a pipe blockage status information data set respectively; the water meter fault comprehensive evaluation module is used to associate the component dirt coverage status information data set with the pipe blockage status information data set to evaluate the fault state of the water meter; the fault warning module is used to compare and analyze the fault state of the water meter to obtain and execute the corresponding fault monitoring and warning instructions; The first monitoring module is used to monitor the water quality status and ultrasonic signal attenuation of each period in the ultrasonic water meter in real time, and obtain a water quality status information data set and an ultrasonic signal propagation status data set after feature extraction, specifically: The first monitoring module includes a water quality monitoring unit and a signal attenuation monitoring unit; the water quality monitoring unit is used to monitor the water quality status of the ultrasonic water meter in real time at each time period, and obtain a water quality status information data set after water quality feature extraction; the water quality feature extraction is performed by identifying and extracting the real-time monitored water quality status information data set to extract key indicators, including water hardness, suspended solids content and turbidity; the signal attenuation monitoring unit is used to monitor the ultrasonic signal attenuation at each time period in real time, and obtain an ultrasonic signal propagation status data set after signal feature extraction; the signal feature extraction is performed by identifying and extracting the real-time monitored ultrasonic signal propagation status data set to extract key indicators, including downstream received signal strength and upstream received signal strength; The pre-analysis module is used to analyze the water quality status information data set and the ultrasonic signal propagation status data set to obtain the water quality index evaluation level and ultrasonic signal attenuation within the corresponding monitoring period, specifically: The pre-analysis module includes a water quality state pre-analysis unit and a signal attenuation pre-analysis unit; the water quality state pre-analysis unit is used to analyze the water quality state information data set, and after dimensionless processing, based on the key indicators of the water quality state and the set weights, to obtain the water quality index evaluation level within the corresponding monitoring period; the signal attenuation pre-analysis unit is used to analyze the ultrasonic signal propagation state data set, and after dimensionless processing, based on the key indicators of the ultrasonic signal and the set weights, to obtain the ultrasonic signal attenuation within the corresponding monitoring period; the dimensionless processing is to normalize the parameters with different units in the water quality state information data set and the ultrasonic signal propagation state data set, and convert them into a unitless pure numerical form; The correlation analysis module is used to correlate the water quality index assessment level and ultrasonic signal attenuation during the corresponding monitoring period to analyze the impact of the water quality index on the signal attenuation during ultrasonic transmission and determine whether to issue a preliminary warning instruction, specifically: The correlation analysis module includes an attenuation correlation analysis unit and a judgment unit; the attenuation correlation analysis unit is used to correlate the water quality index assessment level obtained in the corresponding monitoring period with the ultrasonic signal attenuation, and based on the statistical algorithm of the data distribution characteristics, after dimensionless processing, to analyze the degree of influence of the water quality index on the signal attenuation during the ultrasonic transmission process; the judgment unit is used to determine whether to issue a preliminary warning instruction after comparison based on the degree of influence of the water quality index on the signal attenuation during the ultrasonic transmission process. The specific content is as follows: if the water quality index has an impact on the signal attenuation during the ultrasonic transmission process, a preliminary warning instruction is issued, and the water quality impact will be further analyzed at this time; otherwise, no additional preliminary warning instruction is issued.

2. The ultrasonic water meter fault monitoring and early warning system based on the Internet of Things according to claim 1 is characterized by: The second monitoring module is used to monitor the dirt coverage status information of components and the blockage status information of pipes in the ultrasonic water meter through a plurality of groups of sensors after receiving the preliminary warning instruction, and obtain a component dirt coverage status information data set and a pipe blockage status information data set respectively, specifically: After receiving the preliminary warning instruction, the dirt coverage status information of the components in the ultrasonic water meter is monitored through the camera sensor and the ultrasonic thickness measurement sensor to obtain the component dirt coverage status information data set; The blockage status information in the pipe is monitored by a volumetric flow sensor and an ultrasonic thickness measurement sensor to obtain a data set of the blockage status information in the pipe.

3. The ultrasonic water meter fault monitoring and early warning system based on the Internet of Things according to claim 2 is characterized by: The water meter fault comprehensive evaluation module is used to associate the component dirt coverage status information data set with the pipe blockage status information data set to evaluate the fault status of the water meter. The specific evaluation process is as follows: The water meter fault comprehensive assessment module includes a dirt coverage analysis unit, a pipe blockage analysis unit and a water meter fault assessment unit; Based on the obtained component dirt coverage status information dataset, weights are set for key factors of dirt coverage; The dirt coverage analysis unit generates a calculation formula based on the acquired component dirt coverage status information data set and the set weights after dimensionless processing to analyze the component dirt coverage status.

4. The ultrasonic water meter fault monitoring and early warning system based on the Internet of Things according to claim 3 is characterized by: The pipe obstruction analysis unit sets weights for key factors of pipe obstruction based on the acquired pipe obstruction status information data set; Based on the acquired in-pipe obstruction status information dataset and the set weights, a calculation formula is generated after dimensionless processing to analyze the in-pipe obstruction situation.

5. The ultrasonic water meter fault monitoring and early warning system based on the Internet of Things according to claim 4 is characterized by: The water meter fault assessment unit sets a weight based on the degree of influence of the acquired dirt coverage and pipe obstruction on the fault state of the water meter; The analyzed dirt coverage is correlated with the blockage in the pipe, and after dimensionless processing and combined with the set weights, a calculation formula is generated to evaluate the fault state of the water meter.

6. The ultrasonic water meter fault monitoring and early warning system based on the Internet of Things according to claim 5 is characterized by: The fault warning module is used to compare and analyze the fault status of the water meter to obtain and execute corresponding fault monitoring and warning instructions. The specific process is as follows: The fault warning module includes a comparison unit and a warning unit; The comparison unit is used to compare and analyze the fault status of the water meter to obtain corresponding fault monitoring and early warning instructions. The specific content of the fault monitoring and early warning instructions is as follows: If the water meter is in a fault state, it indicates that the current ultrasonic water meter function state is abnormal and there is a risk of failure. At this time, the first fault monitoring warning instruction is issued; If the water meter is not in a fault state, it means that there is no abnormality in the current function state of the ultrasonic water meter and there is no fault risk. At this time, the second fault monitoring warning instruction is issued; The early warning unit is used to specifically execute the following contents according to receiving the first fault monitoring early warning instruction and the second fault monitoring early warning instruction; When receiving the first environmental monitoring warning instruction, the execution content is to activate the backup water meter, and the system will automatically switch the water pipeline to the backup equipment to ensure the normal supply of water flow; automatically send an alarm notification to the maintenance personnel, inform them of the existing fault risk and specific abnormal conditions via SMS and email, and generate a fault report and send it to the maintenance personnel. The fault report contains water meter fault assessment information, specific information on component dirt coverage status and pipe blockage status, as well as relevant water quality and ultrasonic signal attenuation data information for subsequent maintenance and fault analysis; and activate the sound and light alarm device to alert nearby personnel; When the second environmental monitoring warning instruction is received, the execution content is to record the current monitoring data in the system database as log information of the normal operation of the system for future trend analysis and system debugging. Data collection and analysis continue according to the established monitoring cycle. No additional measures are required and no alarms or notifications are triggered.

7. An ultrasonic water meter fault monitoring and early warning method based on the Internet of Things, used to implement the ultrasonic water meter fault monitoring and early warning system based on the Internet of Things as described in any one of claims 1 to 6, characterized in that: The following steps are included: Step 1: Real-time monitoring of water quality status information and ultrasonic signal attenuation at each time period in the ultrasonic water meter is performed, and after feature extraction, a water quality status information dataset and an ultrasonic signal propagation status dataset are obtained respectively; Step 2: Analyze the water quality status information dataset and the ultrasonic signal propagation status dataset, and correlate the water quality index assessment level obtained during the corresponding monitoring period with the ultrasonic signal attenuation to analyze the impact of the water quality index on the signal attenuation during the ultrasonic transmission process, and determine whether to issue a preliminary warning instruction; Step 3: After receiving the preliminary warning instruction, monitor the dirt coverage status information of the components in the ultrasonic water meter and the blockage status information of the pipe using several sets of sensors, correlate the obtained data sets of the dirt coverage status information of the components and the blockage status information of the pipe, and evaluate the fault status of the water meter; Step 4: Compare and analyze the fault status of the water meter to obtain and execute corresponding fault monitoring and early warning instructions.

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