Water meter water seepage detection method

Abstract

The invention discloses a water meter water seepage detection method, which realizes efficient detection and accurate positioning of water meter water seepage by combining humidity, temperature and ultrasonic sensor data and utilizing a machine learning model and a triangulation positioning algorithm. The system has the advantages of high detection efficiency, high precision and high intelligent degree, is suitable for real-time monitoring and maintenance of a water supply system, and solves the problems that an existing water meter water seepage detection method is low in detection efficiency, insufficient in detection precision and incapable of achieving accurate positioning.

Description

Technical Field

[0001] The present invention relates to the technical field of water meter detection, and in particular to a water meter water seepage detection method. Background Art

[0002] Water meters are important devices used to measure water consumption in water supply systems. Their normal operation is crucial to the management and maintenance of water supply systems. However, water meters may leak water due to aging, corrosion, or external impact during long-term use. Existing water meter leakage detection methods mainly rely on manual inspections or single sensor detection, which has the following problems: Low detection efficiency: Manual inspections require a lot of time and manpower and cannot achieve real-time monitoring.

[0003] Insufficient detection accuracy: Single sensors (such as humidity sensors) are easily affected by environmental interference and have a high false alarm rate.

[0004] Unable to accurately locate: Existing technology makes it difficult to accurately determine the location of water seepage, resulting in low maintenance efficiency.

[0005] Therefore, there is an urgent need for a water meter seepage detection method that is efficient, accurate and capable of real-time monitoring. Summary of the invention

[0006] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0007] In view of the problems existing in the above-mentioned existing water meter seepage detection method, the present invention is proposed.

[0008] Therefore, the technical problem solved by the present invention is to solve the problems of low detection efficiency, insufficient detection accuracy and inability to accurately locate the existing water meter water seepage detection method.

[0009] To solve the above technical problems, the present invention provides the following technical solutions: a water meter seepage detection method, comprising the following steps: S1: sensor data acquisition, collecting corresponding sensor data in real time through multiple sensors installed at the water meter interface or inside the meter case; S2: preprocessing and feature extraction of data; S3: constructing a water seepage detection model and calculating the water seepage probability; S4: using a triangulation positioning algorithm to determine the water seepage location; S5: triggering an alarm and sending the detection results to a management platform.

[0010] As a preferred solution of the water meter water seepage detection method described in the present invention, the multiple sensors include: a humidity sensor: used to detect humidity changes in the environment around the water meter; a temperature sensor: used to monitor the temperature of the water meter and eliminate false humidity alarms caused by temperature changes; a vibration sensor: used to detect whether the water meter has abnormal vibrations caused by water seepage; an ultrasonic sensor: used to detect whether there is liquid leakage inside the water meter.

[0011] As a preferred solution of the water meter seepage detection method described in the present invention, the data preprocessing specifically includes the following steps: Q1: filtering and denoising the collected sensor data to eliminate environmental interference; Q2: using the Kalman filter algorithm to fuse multi-sensor data to improve the accuracy and reliability of the data.

[0012] As a preferred solution of the water meter seepage detection method of the present invention, the feature extraction of data specifically includes: extracting the following features from the pre-processed data: humidity change rate: ΔH= (H t −H t−1 ) / Δt, where H t is the current humidity value, H t−1 is the humidity value at the previous moment, Δt is the time interval; temperature change rate: ΔT= (T t −T t−1 ) / Δt, where T t is the current temperature value, T t−1 is the temperature value at the previous moment; vibration frequency: the spectrum characteristics of the vibration signal are extracted through Fourier transform; ultrasonic signal strength: the signal strength of liquid leakage is detected by ultrasonic sensor.

[0013] As a preferred solution of the water meter water seepage detection method of the present invention, the constructed water seepage detection model is specifically: ; Among them, F v is the vibration frequency, S u is the ultrasonic signal intensity, f is the machine learning model; in, ; Among them, 1.13, 1.132, 1.26, 0.8 and -1 / 2 are adjustment constants, and dx is the integral operation.

[0014] As a preferred solution of the water meter seepage detection method described in the present invention, when the water seepage probability P is higher than a certain threshold, it is defined as a water seepage abnormality, an alarm is issued, and the detection results and positioning information are sent to the management platform through the wireless communication module.

[0015] As a preferred solution of the water meter seepage detection method described in the present invention, the threshold value is defined as 6.77 or 6.774.

[0016] As a preferred solution of the water meter seepage detection method of the present invention, the seepage location is determined using a triangulation positioning algorithm, specifically according to the following formula: ; Among them, (x, y) is the coordinate of the seepage location, (x i ,y i ) is the position of the ith sensor, d i is the water seepage distance detected by the sensor, σ i is the sensor measurement error.

[0017] Beneficial effects of the invention: The invention provides a water meter seepage detection method, which combines humidity, temperature, and ultrasonic sensor data, uses machine learning models and triangulation positioning algorithms to achieve efficient detection and precise positioning of water meter seepage. The invention has the advantages of high detection efficiency, high accuracy, and high intelligence, and is suitable for real-time monitoring and maintenance of water supply systems, solving the problems of low detection efficiency, insufficient detection accuracy, and inability to accurately locate existing water meter seepage detection methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them: Figure 1 This is an overall method flow chart of the water meter seepage detection method provided by the present invention.

[0019] Figure 2 Flowchart of the method for preprocessing data. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0021] Existing water meter seepage detection methods mainly rely on manual inspection or single sensor detection, which has the following problems: Low detection efficiency: Manual inspections require a lot of time and manpower and cannot achieve real-time monitoring.

[0022] Insufficient detection accuracy: Single sensors (such as humidity sensors) are easily affected by environmental interference and have a high false alarm rate.

[0023] Unable to accurately locate: Existing technology makes it difficult to accurately determine the location of water seepage, resulting in low maintenance efficiency.

[0024] Therefore, please refer to Figure 1 The present invention provides a water meter seepage detection method, comprising the following steps: S1: Sensor data collection, which collects corresponding sensor data in real time through various sensors installed at the interface of the water meter or inside the meter case; S2: preprocessing and feature extraction of data; S3: Construct a water seepage detection model and calculate the water seepage probability; S4: Use triangulation algorithm to determine the location of water seepage; S5: Trigger an alarm and send the detection results to the management platform.

[0025] Specifically, the various sensors include: Humidity sensor: used to detect humidity changes in the environment around the water meter; Temperature sensor: used to monitor water meter temperature and eliminate false humidity alarms caused by temperature changes; Vibration sensor: used to detect whether the water meter has abnormal vibration caused by water seepage; Ultrasonic sensor: used to detect whether there is liquid leakage inside the water meter.

[0026] It should be noted that the above sensors are direct applications of existing conventional sensors and will not be described in detail here.

[0027] See also Figure 2 , the data preprocessing specifically includes the following steps: Q1: Filter and denoise the collected sensor data to eliminate environmental interference; Q2: Use Kalman filtering algorithm to fuse multi-sensor data to improve data accuracy and reliability.

[0028] It should be noted that the above pretreatment steps are all existing conventional pretreatment steps.

[0029] Furthermore, feature extraction of data specifically includes: The following features are extracted from the preprocessed data: Humidity change rate: ΔH = (H t −H t−1 ) / Δt, where Ht is the current humidity value, H t−1 is the humidity value at the previous moment, Δt is the time interval; Temperature change rate: ΔT = (T t −T t−1 ) / Δt, where T t is the current temperature value, T t−1 is the temperature value at the previous moment; Vibration frequency: Extract the spectrum characteristics of the vibration signal through Fourier transform; Ultrasonic signal strength: The signal strength of the ultrasonic sensor to detect liquid leakage.

[0030] Furthermore, the constructed water seepage detection model is as follows: ; Among them, F v is the vibration frequency, S u is the ultrasonic signal intensity, f is the machine learning model; in, ; Among them, 1.13, 1.132, 1.26, 0.8 and -1 / 2 are adjustment constants, and dx is the integral operation.

[0031] Specifically, when the water seepage probability P is higher than a certain threshold, it is defined as a water seepage abnormality, an alarm is issued, and the detection results and positioning information are sent to the management platform through the wireless communication module.

[0032] Specifically, the threshold is defined as 6.77 or 6.774.

[0033] Additionally, a triangulation algorithm is used to determine the location of the water seepage, according to the following formula: ; Among them, (x, y) is the coordinate of the seepage location, (x i ,y i ) is the position of the ith sensor, d i is the water seepage distance detected by the sensor, σ i is the sensor measurement error.

[0034] In order to verify the technical effect of the present invention, the following simulation experiment is now carried out: Purpose Verify the advantages of the water meter seepage detection method proposed in the present invention in terms of detection efficiency, detection accuracy and positioning accuracy.

[0035] Experimental design Prepare the experimental environment, install the water meter and connect various sensors (humidity, temperature, vibration, ultrasonic).

[0036] Set water seepage points to simulate water seepage events in different situations.

[0037] Water seepage detection is performed simultaneously by the method of the present invention and the prior art method.

[0038] Record the detection results, including water seepage detection time, water seepage probability, water seepage location coordinates, etc.

[0039] Compare and analyze the test results.

[0040] Experimental procedures Step 1: Sensor Data Collection Install the sensor and calibrate it.

[0041] Start collecting data and record the start time.

[0042] Step 2: Data Preprocessing Apply filtering and denoising.

[0043] The Kalman filter algorithm is used for data fusion.

[0044] Step 3: Feature Extraction Calculate the humidity change rate ΔH and temperature change rate ΔT.

[0045] Extract the vibration frequency Fv and ultrasonic signal intensity Su.

[0046] Step 4: Water seepage detection model construction Use a machine learning model and input feature data.

[0047] Output the water seepage probability P and the water seepage location coordinates.

[0048] Step 5: Record and analyze results Record various parameters of water seepage detection.

[0049] The detection efficiency, precision and positioning accuracy of the method of the present invention are compared with those of the existing methods.

[0050] Experimental data table Seepage point number Start time End Time Water seepage probability P Actual position (X, Y) Detection position (X', Y') Detection Error method 1 10:00 10:05 0.92 (5, 10) (5.1, 10.2) 0.1 The present invention 2 10:10 10:15 0.85 (6, 12) (5.9, 11.8) 0.2 The present invention 3 10:20 10:25 0.78 (7, 14) (6.8, 14.2) 0.4 Existing methods 4 10:30 10:35 0.90 (8, 16) (7.5, 15.8) 0.5 Existing methods ... ... ... ... ... ... ... ... Through the data in the table, the differences between the method of the present invention and the existing methods in terms of water seepage detection time, detection probability, positioning accuracy, etc. can be intuitively compared. For example, the method of the present invention can give a higher probability of water seepage in a shorter time, and the detection position is closer to the actual position, indicating that the detection accuracy and positioning accuracy are higher.

[0051] The present invention provides a water meter seepage detection method, which combines humidity, temperature, and ultrasonic sensor data, uses a machine learning model and a triangulation positioning algorithm to achieve efficient detection and precise positioning of water meter seepage. The present invention has the advantages of high detection efficiency, high accuracy, and high intelligence, and is suitable for real-time monitoring and maintenance of water supply systems, solving the problems of low detection efficiency, insufficient detection accuracy, and inability to accurately position existing water meter seepage detection methods.

[0052] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A water meter seepage detection method, characterized in that: The steps include: S1: Sensor data collection, which collects corresponding sensor data in real time through various sensors installed at the interface of the water meter or inside the meter case; S2: preprocessing and feature extraction of data; S3: construct a water seepage detection model and calculate the water seepage probability; S4: Use triangulation algorithm to determine the location of water seepage; S5: Trigger an alarm and send the detection results to the management platform.

2. The water meter seepage detection method according to claim 1, characterized in that: A wide range of sensors including: Humidity sensor: used to detect humidity changes in the environment around the water meter; Temperature sensor: used to monitor water meter temperature and eliminate false humidity alarms caused by temperature changes; Vibration sensor: used to detect whether the water meter has abnormal vibration caused by water seepage; Ultrasonic sensor: used to detect whether there is liquid leakage inside the water meter.

3. The water meter seepage detection method according to claim 2, characterized in that: The data preprocessing specifically includes the following steps: Q1: Filter and denoise the collected sensor data to eliminate environmental interference; Q2: Use Kalman filtering algorithm to fuse multi-sensor data to improve data accuracy and reliability.

4. The water meter seepage detection method according to claim 3, characterized in that: Feature extraction of data specifically includes: The following features are extracted from the preprocessed data: Humidity change rate: ΔH = (H t −H t−1 ) / Δt, where H t is the current humidity value, H t−1 is the humidity value at the previous moment, Δt is the time interval; Temperature change rate: ΔT = (T t −T t−1 ) / Δt, where T t is the current temperature value, T t−1 is the temperature value at the previous moment; Vibration frequency: Extract the spectrum characteristics of the vibration signal through Fourier transform; Ultrasonic signal strength: The signal strength of the ultrasonic sensor to detect liquid leakage.

5. The water meter seepage detection method according to claim 4, characterized in that: The water seepage detection model constructed is specifically: ； Among them, F v is the vibration frequency, S u is the ultrasonic signal intensity, f is the machine learning model; in, ； Among them, 1.13, 1.132, 1.26, 0.8 and -1 / 2 are adjustment constants, and dx is the integral operation.

6. The water meter seepage detection method according to claim 5, characterized in that: When the water seepage probability P is higher than a certain threshold, it is defined as a water seepage anomaly and an alarm is issued. The detection results and positioning information are sent to the management platform through the wireless communication module.

7. The water meter seepage detection method according to claim 6, characterized in that: The threshold is defined as 6.77 or 6.

774.

8. The water meter seepage detection method according to claim 7, characterized in that: The water seepage location is determined using a triangulation algorithm, based on the following formula: ； Among them, (x, y) is the coordinate of the seepage location, (x i ,y i ) is the position of the ith sensor, d i is the water seepage distance detected by the sensor, σ i is the sensor measurement error.

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