Intelligent water meter multi-perception system

Abstract

This invention relates to a multi-sensor system for smart water meters. The multi-sensor system includes a sensing module, a network transmission module, and a data processing module. The sensing module is installed on the smart water meter and is used to collect and transmit various types of water meter data. The data processing module is installed in the water company and is used to receive, process, and analyze various types of water meter data. The sensing module and the data processing module are connected through the network transmission module. Compared with existing technologies, this invention has advantages such as achieving fusion sensing and data analysis and processing of multiple water meters and sensors through a single system, facilitating simultaneous monitoring and management of various data from multiple smart water meters by water companies, and saving on the management and maintenance costs of smart water meters.

Description

Technical Field

[0001] This invention relates to the field of smart water meter technology, and in particular to a multi-sensor system for smart water meters. Background Technology

[0002] Smart water meters are widely welcomed in the market because they are more intelligent and easier to monitor than traditional water meters. Currently, smart water meters on the market can achieve functions such as water flow data collection and uploading, and remote valve opening and closing. However, these functions are often operated and monitored by separate systems, lacking a unified system platform for centralized monitoring. This makes it inconvenient for water companies to monitor a large number of smart water meters and makes centralized monitoring impossible. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a smart water meter multi-sensor system.

[0004] The objective of this invention can be achieved through the following technical solutions: A multi-sensor system for smart water meters includes a sensing module, a network transmission module, and a data processing module. The sensing module is installed on the smart water meter and is used to collect and transmit various types of water meter data. The data processing module is installed in the water company and is used to receive, process, and analyze various types of water meter data. The sensing module and the data processing module are connected through the network transmission module.

[0005] Furthermore, the sensing module includes a flow sensor, a pressure sensor, a temperature sensor, a water quality sensor, and an abnormal vibration sensor independently installed on the smart water meter; the sensing module also includes a data acquisition unit and a communication unit, the data acquisition unit being used to connect and acquire multi-source sensing data signals from the various sensors mentioned above; the data acquisition unit is connected to the network transmission module through the communication unit.

[0006] Furthermore, the communication unit is a communication unit based on a low-power wide-area wireless communication protocol; the communication unit uses data frame encapsulation, CRC32 check error correction and AES-128 encryption algorithm to ensure transmission security, and combines a sliding window retransmission mechanism to improve reliability, and reduces transmission power consumption and bandwidth usage through data compression algorithm.

[0007] Furthermore, the network transmission module is a transmission module that adopts a converged communication method with NB-IoT as the main component and LoRaWAN as the auxiliary component. The algorithm principle of the network transmission module is as follows: NB-IoT long-distance transmission is achieved based on 3GPP R13 / R14 narrowband modulation technology, the anti-interference capability of LoRaWAN is improved based on CSS spread spectrum modulation technology, transmission parameters are dynamically adjusted through ADR algorithm, power consumption is reduced through sleep wake-up mechanism DRX / eDRX, and the orderly transmission of multi-node data is ensured through routing optimization algorithm.

[0008] Furthermore, the data processing module includes a data receiving unit, a database, a data analysis unit, and a device management platform; the data receiving unit is connected to the network transmission module and is used to receive multi-source sensing data information; the database is connected to the data receiving unit and is used to store the received multi-source sensing data; the data analysis unit is connected to the database and is used to analyze and process the data in the database; the device management platform is connected to the data analysis unit and is used for data visualization and to execute intelligent control strategies in conjunction with the data analysis results.

[0009] Furthermore, the data receiving unit implements data subscription and reception based on the MQTT / CoAP application layer protocol, ensures data reachability through the TCP / UDP transport layer, and uses CRC check, timestamp deduplication, and FIFO buffer queue to implement data preprocessing.

[0010] Furthermore, the algorithm principle of the database is as follows: a time-series database is used to store multi-source sensing data, a composite index is built by the smart water meter device ID + timestamp of each location, and the data is tagged and classified according to sensor type. At the same time, a time-series data compression algorithm is used to reduce storage overhead, and data sharding and partitioning algorithms are used to ensure data read and write efficiency.

[0011] Furthermore, the data analysis unit performs fusion analysis on multi-source sensing data. Its algorithm principle is as follows: temperature / pressure compensation algorithm is used to correct flow measurement error, threshold judgment + isolated forest algorithm is used to realize anomaly detection, FFT frequency domain analysis is used to identify vibration fault characteristics, and minimum flow method + trend fitting algorithm is used to realize water leakage early warning.

[0012] Furthermore, the equipment management platform includes functions such as data visualization, multi-level alarm and early warning, remote control, operation and maintenance management, energy consumption statistical analysis, automatic report generation, hierarchical permission management, and equipment lifecycle management; the intelligent control strategy includes automatic valve shut-off by smart water meters in case of abnormalities and low battery warning.

[0013] Compared with the prior art, the present invention has the following advantages: This invention designs a multi-sensor system that centrally transmits data from multiple sensors to a single processing system for centralized analysis and processing. This significantly improves the monitoring efficiency of smart water meters, facilitating centralized management and control of multiple smart water meters by water companies. When a water meter malfunctions, the system can quickly and accurately pinpoint the location and cause of the malfunction, thereby sending fault information to maintenance personnel, improving maintenance efficiency, and reducing maintenance costs. Attached Figure Description

[0014] Figure 1 The structure diagram of the multi-sensor system provided by the present invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0016] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0017] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0018] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of this invention is usually placed during use. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0019] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0020] Furthermore, terms such as "horizontal" and "vertical" do not imply that components must be absolutely horizontal or suspended, but rather that they can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," not that the structure must be completely horizontal, but can be slightly tilted. Example

[0021] like Figure 1 As shown, a multi-sensor system for smart water meters includes a sensing module, a network transmission module, and a data processing module. The sensing module is installed on the smart water meter and is used to collect and transmit various types of water meter data. The data processing module is installed in the water company department and is used to receive, process, and analyze various types of water meter data. The sensing module and the data processing module are connected through the network transmission module.

[0022] The sensing module includes a flow sensor, pressure sensor, temperature sensor, water quality sensor, and abnormal vibration sensor independently installed on the smart water meter, sensing multi-source data from the smart water meter through multiple sensors. The sensing module also includes a data acquisition unit and a communication unit. The data acquisition unit connects to and acquires multi-source sensing data signals from the aforementioned sensors. The data acquisition unit connects to the network transmission module through the communication unit. The communication unit is based on a low-power wide-area wireless communication protocol. The communication unit employs data frame encapsulation, CRC32 error correction, and AES-128 encryption algorithms to ensure transmission security, and combines this with an ARQ (Augmented Real-Time Request) sliding window retransmission mechanism to improve reliability. Data compression algorithms reduce transmission power consumption and bandwidth usage.

[0023] The network transmission module is a transmission module that uses NB-IoT as the main communication method and LoRaWAN as the auxiliary communication method. The algorithm principle of the network transmission module is as follows: NB-IoT long-distance transmission is achieved based on 3GPP R13 / R14 narrowband modulation technology, LoRaWAN anti-interference is improved based on CSS spread spectrum modulation technology, transmission parameters are dynamically adjusted through ADR (Adaptive Data Rate) algorithm, power consumption is reduced through sleep wake-up mechanism DRX / eDRX, and orderly data transmission of multiple nodes is ensured through routing optimization algorithm.

[0024] The data processing module includes a data receiving unit, a database, a data analysis unit, and a device management platform. The data receiving unit is connected to the network transmission module and is used to receive multi-source sensing data. The database is connected to the data receiving unit and is used to store the received multi-source sensing data. The data analysis unit is connected to the database and is used to analyze and process the data in the database. The device management platform is connected to the data analysis unit and is used for data visualization and to execute intelligent control strategies based on the data analysis results. The data receiving unit implements data subscription and reception based on the MQTT / CoAP application layer protocol, ensures data reachability through the TCP / UDP transport layer, and uses CRC checksum, timestamp deduplication, and FIFO buffer queues for data preprocessing. The algorithm principle of the database is as follows: Multi-source sensing data is stored using a time-series database. A composite index is constructed using the smart water meter device ID + timestamp from various locations. Data is tagged and categorized by sensor type (e.g., flow sensor, pressure sensor, temperature sensor, water quality sensor, etc.). A time-series data compression algorithm is used to reduce storage overhead, and data sharding and partitioning algorithms ensure efficient reading and writing of massive amounts of data. The data analysis unit performs fusion analysis on the multi-source sensing data. Its algorithm principle is as follows: A temperature / pressure compensation algorithm (linear regression + table lookup interpolation) is used to correct flow measurement errors. Anomaly detection, such as leakage, overpressure, and water quality exceeding standards, is achieved based on threshold judgment and the isolated forest algorithm. Vibration fault characteristics are identified through FFT frequency domain analysis, and leakage early warning is achieved through the minimum flow method and trend fitting algorithm.

[0025] The equipment management platform includes data visualization, multi-level alarm and early warning, remote control, operation and maintenance management, energy consumption statistical analysis, automatic report generation, hierarchical permission management, and equipment lifecycle management functions. The multi-level alarm and early warning includes proactive reporting, SMS, and APP push notifications. Remote control includes valve switching, parameter configuration, and firmware upgrades. Operation and maintenance management includes automatic work order dispatch, equipment location, and fault tracing. The intelligent control strategy includes automatic valve closure by smart water meters in case of abnormalities and low battery warnings.

[0026] The working steps of the multi-sensor system of the present invention are as follows: 1) Real-time sensing and signal acquisition by multiple sensors: The flow sensor, pressure sensor, temperature sensor and water quality sensor installed on the smart water meter start sensing simultaneously to capture physical quantities such as water flow speed, pipeline pressure, water temperature and water quality; the data acquisition unit receives the analog signals output by each sensor, converts them into digital signals through analog-to-digital conversion, and performs preliminary noise reduction processing to eliminate invalid signals caused by environmental interference.

[0027] 2) Data encapsulation, encryption and network transmission: The communication unit encapsulates the pre-processed digital signal into standard data frames according to a unified protocol, and adds device ID, timestamp and sensor type label; it verifies data integrity through CRC32 check algorithm, ensures data security through AES-128 encryption algorithm, and optimizes transmission reliability through sliding window retransmission mechanism; it sends the data to the data processing module through network transmission module, and enables sleep wake-up mechanism (DRX / eDRX) during transmission to reduce device power consumption.

[0028] 3) Data Reception and Preprocessing: The data receiving unit of the data processing module subscribes to and receives transmitted data through the MQTT / CoAP application layer protocol, and the data reachability is guaranteed by the TCP / UDP transport layer; the received data is subjected to secondary verification (CRC check + protocol parsing), duplicate data is removed by the timestamp deduplication algorithm, and valid data is temporarily stored in the FIFO cache queue, completing the preprocessing process of "reception-verification-deduplication-caching" to ensure data compliance.

[0029] 4) Data classification, storage and index construction: The pre-processed valid data is pushed to the time series database. The system builds a composite index according to "device ID + timestamp + sensor type" and stores flow data, pressure data, temperature data, water quality data, vibration data and other data separately with labels. At the same time, the Gorilla time series data compression algorithm is used to reduce storage overhead, and data sharding and partitioning algorithms are used to ensure the efficiency of subsequent data reading, writing and querying.

[0030] 5) Multi-source data fusion analysis and anomaly identification: The data analysis unit retrieves various sensor data from the time-series database. First, it executes a temperature / pressure compensation algorithm using linear regression and table lookup interpolation to correct flow measurement errors and improve measurement accuracy. Then, it uses a "threshold judgment + isolated forest algorithm" to perform cross-analysis on multi-dimensional data—for example, it uses the combination of sudden flow change and sudden pressure drop to judge water leakage and water quality indicators exceeding the standard to trigger water quality anomalies. At the same time, it uses the minimum flow method and trend fitting algorithm to predict potential risks, and finally generates analysis results and fault type labels of "normal / mild anomaly / severe anomaly", such as water leakage, overpressure, and water quality exceeding the standard.

[0031] 6) Data visualization and tiered alarm triggering: The equipment management platform receives the structured results output by the data analysis unit and visualizes information such as cumulative flow, real-time pressure, water temperature, water quality compliance, and equipment operating status in the form of real-time dashboards, trend curves, and data reports. At the same time, it triggers corresponding alarm mechanisms according to the level of abnormality: minor abnormalities only display a warning icon on the platform, while serious abnormalities simultaneously initiate proactive reporting to the local platform and push SMS / APP to maintenance personnel, and automatically generate maintenance work orders containing equipment location, fault type, and abnormal data screenshots.

[0032] 7) Remote control command issuance and execution feedback: The system automatically triggers feedback actions based on the analysis results: If an emergency such as a serious water leak or excessive toxicity in the water is detected, the equipment management platform issues an "automatic valve shut-off" command to the smart water meter through the converged communication network, and the smart water meter automatically shuts off the valve; if it is necessary to optimize the equipment operation, commands such as adjusting the sampling frequency and calibration parameters can be issued; after the smart water meter executes the command, it sends feedback information such as valve status and parameter update results back to the data processing system, and the platform updates the equipment execution status in real time, forming a control closed loop of "analysis-command-execution-feedback".

[0033] 8) Data archiving and system optimization iteration: Historical data (including raw data, analysis results, control records, and alarm logs) are archived to a time-series database for long-term storage according to a preset cycle, supporting subsequent traceability and query; the system regularly mines historical data patterns through big data analysis, optimizes algorithm parameters, and iterates equipment management strategies (such as optimizing sampling frequency and adjusting alarm triggering conditions) to continuously improve the system's metering accuracy, anomaly identification accuracy, and operation and maintenance efficiency.

[0034] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A multi-sensor system for smart water meters, characterized in that, The multi-sensor system includes a sensing module, a network transmission module, and a data processing module. The sensing module is installed on the smart water meter and is used to collect and transmit various types of water meter data. The data processing module is installed in the water company department and is used to receive, process, and analyze various types of water meter data. The sensing module and the data processing module are connected through the network transmission module.

2. The multi-sensor system for smart water meters according to claim 1, characterized in that, The sensing module includes a flow sensor, pressure sensor, temperature sensor, water quality sensor, and abnormal vibration sensor independently installed on the smart water meter; the sensing module also includes a data acquisition unit and a communication unit, the data acquisition unit being used to connect and acquire multi-source sensing data signals from the above-mentioned sensors; the data acquisition unit is connected to the network transmission module through the communication unit.

3. The multi-sensor system for a smart water meter according to claim 2, characterized in that, The communication unit is based on a low-power wide-area wireless communication protocol. The communication unit uses data frame encapsulation, CRC32 check error correction and AES-128 encryption algorithm to ensure transmission security, and combines a sliding window retransmission mechanism to improve reliability. It also reduces transmission power consumption and bandwidth usage through data compression algorithm.

4. The intelligent water meter multi-sensor system according to claim 3, characterized in that, The network transmission module is a converged communication module that uses NB-IoT as the primary communication method and LoRaWAN as the secondary communication method. The algorithm principle of the network transmission module is as follows: it realizes long-distance transmission of NB-IoT based on 3GPP R13 / R14 narrowband modulation technology, improves the anti-interference of LoRaWAN based on CSS spread spectrum modulation technology, dynamically adjusts transmission parameters through ADR algorithm, reduces power consumption through sleep wake-up mechanism DRX / eDRX, and ensures orderly transmission of data from multiple nodes through routing optimization algorithm.

5. The multi-sensor system for a smart water meter according to claim 4, characterized in that, The data processing module includes a data receiving unit, a database, a data analysis unit, and a device management platform; the data receiving unit is connected to the network transmission module and is used to receive multi-source sensing data information; the database is connected to the data receiving unit and is used to store the received multi-source sensing data. The data analysis unit is connected to the database and is used to analyze and process the data in the database. The device management platform is connected to the data analysis unit for data visualization and for executing intelligent control strategies in conjunction with the data analysis results.

6. The multi-sensor system for a smart water meter according to claim 5, characterized in that, The data receiving unit implements data subscription and reception based on the MQTT / CoAP application layer protocol, ensures data reachability through the TCP / UDP transport layer, and uses CRC check, timestamp deduplication, and FIFO buffer queue to implement data preprocessing.

7. A multi-sensor system for smart water meters according to claim 6, characterized in that, The algorithm principle of the database is as follows: a time-series database is used to store multi-source sensing data. A composite index is built by combining the smart water meter device ID and timestamp. The data is tagged and classified according to sensor type. At the same time, a time-series data compression algorithm is used to reduce storage overhead, and data sharding and partitioning algorithms are used to ensure data read and write efficiency.

8. The multi-sensor system for a smart water meter according to claim 7, characterized in that, The data analysis unit performs fusion analysis on multi-source sensing data. Its algorithm principle is as follows: temperature / pressure compensation algorithm is used to correct flow measurement error, threshold judgment + isolated forest algorithm is used to realize anomaly detection, FFT frequency domain analysis is used to identify vibration fault characteristics, and minimum flow method + trend fitting algorithm is used to realize water leakage early warning.

9. A multi-sensor system for smart water meters according to claim 8, characterized in that, The equipment management platform includes functions such as data visualization, multi-level alarm and early warning, remote control, operation and maintenance management, energy consumption statistical analysis, automatic report generation, hierarchical permission management, and equipment lifecycle management; the intelligent control strategy includes automatic valve shut-off by smart water meters in case of abnormalities and low battery warning.

Images