Multi-dimensional monitoring alarm and intelligent water affair management system and method based on MQTT protocol

Abstract

The invention provides a multi-dimensional monitoring alarm and intelligent water affair management system and method based on an MQTT protocol, and relates to the technical field of intelligent water affair management, and the method comprises the steps: carrying out the data collection of a water affair system based on a sensor network, and generating target water affair data; performing format conversion on the target water affair data based on an MQTT protocol, and transmitting the target water affair data to an MQTT server side through an Internet of Things gateway; performing multi-dimensional analysis on the target water affair data based on the MQTT server side to obtain a multi-dimensional data analysis result; adjusting a water affair management strategy in real time according to a multi-dimensional data analysis result; according to the method, the preset alarm condition is obtained, and the fault monitoring is performed on the water affair system according to the preset alarm condition and the multi-dimensional data analysis result, so that the accurate monitoring, timely alarm and intelligent management of the water affair system can be realized, the water affair management efficiency is improved, and the reasonable utilization of water resources and the stable operation of the water affair system are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent water management, and in particular to a multi-dimensional monitoring alarm and intelligent water management system and method based on the MQTT protocol. Background Art

[0002] With the acceleration of urbanization and the growing demand for water resources management, the intelligence and automation of water management systems have become an inevitable trend in the development of the industry.

[0003] Traditional water management systems usually rely on manual regular inspections for data collection, which is often inefficient and unable to obtain data in real time. It is difficult to fully grasp the dynamic changes of the water system, and it is impossible to achieve optimal allocation of water resources and efficient scheduling of equipment, which leads to waste of water resources and increased operating costs. In addition, the system lacks a unified and efficient transmission protocol, which easily causes data loss and delay, and cannot make timely judgments on abnormal water situations. At the same time, the existing technology mainly relies on manual experience for fault judgment, lacks scientific threshold setting and intelligent analysis, and cannot detect system failures in a timely manner.

[0004] Therefore, it is necessary to provide a multi-dimensional monitoring alarm and intelligent water management system and method based on the MQTT protocol to solve the above technical problems. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a multi-dimensional monitoring alarm and intelligent water management system and method based on the MQTT protocol, which is used to solve the problem that traditional water management systems usually rely on manual periodic inspections for data collection. This method is often inefficient and cannot obtain data in real time, making it difficult to fully grasp the dynamic changes of the water system, and unable to achieve optimal allocation of water resources and efficient scheduling of equipment, which in turn leads to waste of water resources and increased operating costs. In addition, the system lacks a unified and efficient transmission protocol, which easily causes data loss and delay, and cannot make timely judgments on water abnormalities. At the same time, the existing technology mainly relies on manual experience for fault judgment, lacks scientific threshold setting and intelligent analysis, and cannot timely detect system failures.

[0006] The multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol provided by the present invention includes: A data collection module is used to collect data from the water system based on a sensor network and generate target water data; A conversion and transmission module, used for converting the format of the target water service data based on the MQTT protocol, and transmitting the format to the MQTT server through the Internet of Things gateway; A data analysis module, used to perform multi-dimensional analysis on the target water affairs data based on the MQTT server to obtain multi-dimensional data analysis results; A strategy adjustment module, used to adjust the water management strategy of the water system in real time according to the multi-dimensional data analysis results; The fault monitoring module is used to obtain preset alarm conditions and perform fault monitoring on the water system according to the preset alarm conditions and the multi-dimensional data analysis results.

[0007] Preferably, the data acquisition module is used to collect data from the water system based on the sensor network to generate target water data, specifically including: The sensor network includes a water quality sensor, a flow sensor and a pressure sensor; The water quality analog signal of the water source corresponding to the water system is collected based on the water quality sensor; the flow analog signal of the water plant corresponding to the water system is collected based on the flow sensor; the pressure analog signal of the water transmission and distribution network corresponding to the water system is collected based on the pressure sensor; Aggregating the water quality simulation signal, the flow simulation signal and the pressure simulation signal to generate a water affairs simulation signal; Performing analog-to-digital conversion on the water affairs analog signal to obtain a water affairs digital signal, and encapsulating the water affairs digital signal to obtain the target water affairs data; The target water service data includes target water quality data, target flow data and target pressure data.

[0008] Preferably, the step of performing analog-to-digital conversion on the water affairs analog signal to obtain a water affairs digital signal specifically includes: The analog-to-digital conversion reference voltage and the analog-to-digital conversion bit number are obtained, and the water service analog signal is converted into a digital form. The calculation formula of the water service digital signal is as follows: In the formula, Indicates water service digital signal; Indicates water service analog signal; represents the analog-to-digital conversion reference voltage; f represents the number of analog-to-digital conversion bits.

[0009] Preferably, the conversion and transmission module is used to convert the format of the target water service data based on the MQTT protocol and transmit it to the MQTT server through the Internet of Things gateway, specifically including: Based on the MQTT protocol, the data format of the target water service data is converted into the MQTT message format, and transmitted to the MQTT server through the Internet of Things gateway, and the MQTT server is equipped with a load balancing device; A heartbeat reconnection mechanism is set in the Internet of Things gateway and the MQTT server, the Internet of Things gateway sends a heartbeat packet to the MQTT server according to the heartbeat interval, and records the heartbeat sending time when the Internet of Things gateway sends the heartbeat packet and the heartbeat receiving time when the MQTT server receives the heartbeat packet; If the heartbeat waiting time between the heartbeat sending time and the heartbeat receiving time exceeds the heartbeat timeout threshold, the heartbeat reconnection mechanism is triggered, and the Internet of Things gateway and the MQTT server are reconnected.

[0010] Preferably, the data analysis module is used to perform multi-dimensional analysis on the target water service data based on the MQTT server to obtain multi-dimensional data analysis results, specifically including: The target water quality data set is set as , represents the i-th target water quality data; n represents the number of target water quality data; Obtain a preset cluster number K, randomly select K target water quality data as cluster centers, and the data set composed of the cluster centers is , represents the hth cluster center; For the target water quality data , calculate the target water quality data To cluster center Distance as follows: In the formula, Indicates target water quality data To cluster center distance; J represents the target water quality data The characteristic dimension of Indicates target water quality data The jth feature of Represents the cluster center The jth feature of The target water quality data Assign to the nearest cluster center The corresponding cluster , and the target water quality data To the nearest cluster center The distances are as follows: In the formula, Indicates target water quality data To the nearest cluster center distance; Indicates target water quality data To cluster center The distance between the two groups is ; K represents the preset number of clusters; Compute clusters The corresponding new cluster center as follows: In the formula, Representation clustering The corresponding new cluster center; represents the hth cluster; Representation clustering The number of target water quality data; represents the i-th target water quality data; The objective function is calculated as follows: Where, J represents the objective function; represents the i-th target water quality data; represents the hth cluster center; represents the hth cluster; K represents the preset number of clusters; Indicates target water quality data To cluster center The Euclidean distance of Iteratively update the cluster center until the change value of the objective function before and after the iteration is less than a preset iteration threshold, or the objective function reaches a maximum number of iterations, stop the iteration operation, and divide the target water quality data into different clusters, and determine the water quality change trend corresponding to the target water quality data according to the clustering result; Otherwise, the dataset composed of new cluster centers As the current cluster center, and repeat the above iterative operation.

[0011] Preferably, a water volume prediction model of the water system is constructed, and future flow data is predicted based on the target flow data. The corresponding calculation formula is as follows: In the formula, represents the future traffic data at time t; represents the moving average partial polynomial; q represents the moving average order, that is, the amount of white noise; represents a white noise sequence; represents the autoregressive partial polynomial; p represents the autoregressive order, that is, the number of target flow data; B represents the backshift operator; A represents the difference order.

[0012] Preferably, constructing a fault prediction model for the water system and predicting the system fault probability of the water system according to the target pressure data specifically includes: The target pressure data is input into the input layer of the fault prediction model, and the input value of the u-th node in the hidden layer of the fault prediction model is as follows: In the formula, represents the input value of the u-th node in the hidden layer of the fault prediction model; R represents the number of target pressure data in the input layer; Represents the weight of the rth target pressure data in the input layer to the uth node in the hidden layer; Represents the rth target pressure data in the input layer; represents the bias term of the u-th node in the hidden layer; The corresponding output value of the u-th node in the hidden layer is as follows: In the formula, Represents the output value of the u-th node in the hidden layer of the fault prediction model; represents the input value of the u-th node in the hidden layer of the fault prediction model; e represents a natural constant; The input values ​​of the output layer of the fault prediction model are as follows: In the formula, represents the input value of the output layer of the fault prediction model; U represents the number of nodes in the hidden layer; represents the weight from the uth node in the hidden layer to the output layer; Represents the output value of the u-th node in the hidden layer of the fault prediction model; Represents the bias term of the output layer; The corresponding output of the output layer is as follows: In the formula, Represents the output value of the output layer of the fault prediction model; represents the input value of the output layer of the fault prediction model; e represents a natural constant; The output value of the output layer is the system failure probability.

[0013] Preferably, the preset alarm conditions include water quality alarm conditions, flow alarm conditions and pressure alarm conditions; When the water quality change trend meets the water quality alarm condition, the future flow data meets the flow alarm condition, or the system failure probability meets the pressure alarm condition, it is determined that the water system has a failure and the system alarm mechanism of the water system is triggered.

[0014] A multi-dimensional monitoring alarm and intelligent water management method based on the MQTT protocol, the method comprising: Collect data from the water system based on the sensor network to generate target water data; The target water service data is formatted based on the MQTT protocol and transmitted to the MQTT server through the IoT gateway; Based on the MQTT server, a multi-dimensional analysis is performed on the target water service data to obtain a multi-dimensional data analysis result; According to the multi-dimensional data analysis results, the water management strategy of the water system is adjusted in real time; Acquire preset alarm conditions, and perform fault monitoring on the water system according to the preset alarm conditions and the multi-dimensional data analysis results.

[0015] Compared with the related art, the multi-dimensional monitoring alarm and intelligent water management system and method based on the MQTT protocol provided by the present invention has the following beneficial effects: The present invention collects data from the water system based on a sensor network to generate target water data; converts the format of the target water data based on the MQTT protocol, and transmits it to the MQTT server through the Internet of Things gateway; based on the MQTT server, performs multi-dimensional analysis on the target water data to obtain multi-dimensional data analysis results; according to the multi-dimensional data analysis results, the water management strategy of the water system is adjusted in real time; the preset alarm conditions are obtained, and the water system is monitored for faults according to the preset alarm conditions and the multi-dimensional data analysis results. In this way, the advantages of the MQTT protocol can be utilized, combined with multi-dimensional data processing and intelligent decision-making technology, to achieve accurate monitoring, timely alarm and intelligent management of the water system, improve the efficiency and quality of water management, and ensure the rational use of water resources and the stable operation of the water system.

[0016] The present invention can realize comprehensive, real-time acquisition and stable transmission of water data through multi-source data collection and MQTT protocol transmission; and can perform multi-dimensional analysis of water data to provide a scientific basis for intelligent alarm and management decision-making; the system of the present invention has intelligent management decision-making functions, which can realize the optimal allocation of water resources and efficient management of equipment; in addition, the system of the present invention ensures the timely discovery and handling of abnormal situations through an intelligent alarm mechanism, thereby improving the level of refinement of water management, ensuring the safe and stable operation of the water system, and promoting the sustainable use of water resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a system block diagram of the multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol of the present invention; Figure 2 A schematic diagram of sending a heartbeat packet of the present invention; Figure 3 This is a flow chart of the multi-dimensional monitoring alarm and intelligent water management method based on the MQTT protocol of the present invention. DETAILED DESCRIPTION

[0018] The present invention will be further described below in conjunction with the accompanying drawings and implementation modes.

[0019] Embodiment 1

[0020] like Figure 1 As shown, a multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol includes: A data collection module is used to collect data from the water system based on a sensor network and generate target water data; The sensor network refers to a network composed of multiple sensors, which are deployed at key locations in the water system to collect various water data. The target water data refers to the real-time data of the water system collected by various sensors.

[0021] In practical applications, multiple sensors are deployed at key locations in the water system, such as water sources, water plants, and water distribution networks, to form a sensor network. These sensors can collect water-related data, such as water quality data at water sources, flow data at water plants, and pressure data at water distribution networks, and finally aggregate them to generate target water data.

[0022] A conversion and transmission module, used for converting the format of the target water service data based on the MQTT protocol, and transmitting the format to the MQTT server through the Internet of Things gateway; Among them, the MQTT protocol is a lightweight IoT transmission protocol with the characteristics of low bandwidth usage and support for message publishing and subscription modes, which can ensure stable and fast data transmission in complex network environments. The IoT gateway refers to a device used to connect the sensor network and the MQTT server, which has the function of data format conversion and transmission. The MQTT server refers to a device used to receive water service data transmitted by the IoT gateway based on the MQTT protocol.

[0023] It is understandable that the collected water data can be converted in format according to the requirements of the MQTT protocol to make it conform to the transmission standard of the MQTT protocol. After the conversion is completed, the data can be sent to the MQTT server in the form of MQTT messages through the IoT gateway to ensure the stability and efficiency of data transmission.

[0024] A data analysis module, used to perform multi-dimensional analysis on the target water affairs data based on the MQTT server to obtain multi-dimensional data analysis results; It is understandable that after receiving the water data, the MQTT server can conduct in-depth analysis of the water data from multiple dimensions through data processing technology to obtain multi-dimensional data analysis results.

[0025] A strategy adjustment module, used to adjust the water management strategy of the water system in real time according to the multi-dimensional data analysis results; In the water system, water management strategies specifically include rational allocation of water resources, arrangement of equipment maintenance plans, etc.

[0026] The fault monitoring module is used to obtain preset alarm conditions and perform fault monitoring on the water system according to the preset alarm conditions and the multi-dimensional data analysis results.

[0027] Among them, the preset alarm conditions refer to the conditions preset in advance for judging whether there is a fault in the water system and whether to trigger the system alarm mechanism. The fault monitoring module can obtain the preset alarm conditions and combine the multi-dimensional water data analysis results to monitor the water system for faults. Once an abnormality is found, an alarm will be issued in time.

[0028] In the specific implementation process, the data acquisition module is used to collect data from the water system based on the sensor network to generate target water data, specifically including: The sensor network includes a water quality sensor, a flow sensor and a pressure sensor; The water quality analog signal of the water source corresponding to the water system is collected based on the water quality sensor; the flow analog signal of the water plant corresponding to the water system is collected based on the flow sensor; the pressure analog signal of the water transmission and distribution network corresponding to the water system is collected based on the pressure sensor; Aggregating the water quality simulation signal, the flow simulation signal and the pressure simulation signal to generate a water affairs simulation signal; Performing analog-to-digital conversion on the water affairs analog signal to obtain a water affairs digital signal, and encapsulating the water affairs digital signal to obtain the target water affairs data; The target water service data includes target water quality data, target flow data and target pressure data.

[0029] It can be understood that a water quality sensor refers to a device used to collect water quality-related information from water sources in a water system and convert physical quantities of water quality into electrical signals. A flow sensor refers to a device used to obtain water flow data from a water plant in a water system and convert flow values ​​into measurable electrical signals. A pressure sensor refers to a device used to monitor the pressure of a water distribution network in a water system and convert pressure values ​​into electrical signals.

[0030] Water quality analog signal refers to the electrical signal used to reflect the water quality of the water source. Flow analog signal refers to the electrical signal used to reflect the water flow of the water plant. Pressure analog signal refers to the electrical signal used to reflect the pressure state of the water distribution network. Water service analog signal refers to the electrical signal used to reflect the comprehensive operation status of the water service system.

[0031] Water supply digital signal refers to the signal obtained by analog-to-digital conversion of water supply analog signal, which is represented in discrete digital form and can be processed by computer system. After encapsulation and processing of water supply digital signal, target water quality data can be obtained, which can reflect the water quality of water source. By sorting and encapsulating water supply digital signal, target flow data can be obtained, which can reflect the water flow information of water plant. After encapsulation and processing of water supply digital signal, target pressure data can be obtained, which can show the pressure condition of water supply and distribution network.

[0032] In the water supply system, water quality sensors are deployed at the water source, flow sensors are deployed at the water plant, and pressure sensors are deployed in the water supply and distribution network. The water quality sensor can collect water quality analog signals from the water source, the flow sensor can collect flow analog signals from the water plant, and the pressure sensor can collect pressure analog signals from the water supply and distribution network. Furthermore, the analog signals collected by the water quality sensor, flow sensor, and pressure sensor can be aggregated to form a unified water supply analog signal.

[0033] The analog-to-digital conversion device can convert the aggregated water service analog signal into a water service digital signal. The analog-to-digital conversion operation can convert the continuous analog signal into a discrete digital form, which is convenient for subsequent computer system processing and storage.

[0034] By encapsulating the water service digital signals, that is, sorting and classifying the water service digital signals according to a specific data format, target water service data including target water quality data, target flow data and target pressure data can be obtained.

[0035] The step of performing analog-to-digital conversion on the water affairs analog signal to obtain the water affairs digital signal specifically includes: The analog-to-digital conversion reference voltage and the analog-to-digital conversion bit number are obtained, and the water service analog signal is converted into a digital form. The calculation formula of the water service digital signal is as follows: In the formula, Indicates water service digital signal; Indicates water service analog signal; represents the analog-to-digital conversion reference voltage; f represents the number of analog-to-digital conversion bits.

[0036] The analog-to-digital conversion reference voltage refers to the voltage value used as a reference standard in the analog-to-digital conversion process, which is used to calculate the water service digital signal. The number of bits in the analog-to-digital conversion refers to the parameter used to determine the accuracy of the analog-to-digital conversion. The higher the number of bits, the more accurately the converted digital signal can reflect the analog signal.

[0037] It is understandable that the reference voltage and the number of conversion bits required for analog-to-digital conversion can be obtained first. Then, the water service analog signal can be converted into a water service digital signal based on the reference voltage and the number of conversion bits, and the converted water service digital signal can be preliminarily processed to remove possible abnormal values ​​and improve data quality. Furthermore, the accuracy of the converted water service digital signal can be checked to ensure that it can effectively reflect the characteristics of the water service analog signal.

[0038] The conversion and transmission module is used to convert the format of the target water service data based on the MQTT protocol and transmit it to the MQTT server through the Internet of Things gateway, specifically including: Based on the MQTT protocol, the data format of the target water service data is converted into the MQTT message format, and transmitted to the MQTT server through the Internet of Things gateway, and the MQTT server is equipped with a load balancing device; A heartbeat reconnection mechanism is set in the Internet of Things gateway and the MQTT server, the Internet of Things gateway sends a heartbeat packet to the MQTT server according to the heartbeat interval, and records the heartbeat sending time when the Internet of Things gateway sends the heartbeat packet and the heartbeat receiving time when the MQTT server receives the heartbeat packet; If the heartbeat waiting time between the heartbeat sending time and the heartbeat receiving time exceeds the heartbeat timeout threshold, the heartbeat reconnection mechanism is triggered, and the Internet of Things gateway and the MQTT server are reconnected.

[0039] The load balancing device is a device used to distribute the load of the MQTT server, which is used to ensure that the server maintains stable and efficient operation when a large amount of concurrent data is transmitted. The heartbeat reconnection mechanism is a mechanism that monitors the network connection status by sending heartbeat packets. When the network connection is abnormal, the heartbeat reconnection mechanism will be automatically triggered, and the IoT gateway and the MQTT server will be reconnected to ensure that data transmission is not interrupted.

[0040] In practical applications, the original format of water data can be converted into the MQTT message format according to the requirements of the MQTT protocol. Then, the format-converted data can be sent to the MQTT server through the IoT gateway, which is equipped with a load balancing device to ensure the standardization and efficiency of data transmission.

[0041] Configure the heartbeat reconnection mechanism in the IoT gateway and MQTT server. Figure 2 As shown, the IoT gateway can send heartbeat packets to the MQTT server at regular intervals according to the set heartbeat interval, and record the sending and receiving times of the heartbeat packets respectively.

[0042] Furthermore, the heartbeat waiting time between the heartbeat sending time and the heartbeat receiving time can be calculated and compared with the pre-set heartbeat timeout threshold. Once the heartbeat waiting time exceeds the heartbeat timeout threshold, the heartbeat reconnection mechanism will be triggered immediately, and the IoT gateway and the MQTT server will be reconnected to ensure the continuity of data transmission.

[0043] The data analysis module is used to perform multi-dimensional analysis on the target water affairs data based on the MQTT server to obtain multi-dimensional data analysis results, specifically including: The target water quality data set is set as , represents the i-th target water quality data; n represents the number of target water quality data; Obtain a preset cluster number K, randomly select K target water quality data as cluster centers, and the data set composed of the cluster centers is , represents the hth cluster center; For the target water quality data , calculate the target water quality data To cluster center Distance as follows: In the formula, Indicates target water quality data To cluster center distance; J represents the target water quality data The characteristic dimension of Indicates target water quality data The jth feature of Represents the cluster center The jth feature of The target water quality data Assign to the nearest cluster center The corresponding cluster , and the target water quality data To the nearest cluster center The distances are as follows: In the formula, Indicates target water quality data To the nearest cluster center distance; Indicates target water quality data To cluster center The distance between the two groups is ; K represents the preset number of clusters; Compute clusters The corresponding new cluster center as follows: In the formula, Representation clustering The corresponding new cluster center; represents the hth cluster; Representation clustering The number of target water quality data; represents the i-th target water quality data; The objective function is calculated as follows: Where, J represents the objective function; represents the i-th target water quality data; represents the hth cluster center; represents the hth cluster; K represents the preset number of clusters; Indicates target water quality data To cluster center The Euclidean distance of Iteratively update the cluster center until the change value of the objective function before and after the iteration is less than a preset iteration threshold, or the objective function reaches a maximum number of iterations, stop the iteration operation, and divide the target water quality data into different clusters, and determine the water quality change trend corresponding to the target water quality data according to the clustering result; Otherwise, the dataset composed of new cluster centers As the current cluster center, and repeat the above iterative operation.

[0044] Among them, a preset number of clusters can be obtained, and a corresponding number of data can be randomly selected from the data set corresponding to the target water quality data as cluster centers to form a cluster center data set. For each target water quality data, its distance to each cluster center can be calculated, and according to the calculation result, the target water quality data can be assigned to the cluster corresponding to the cluster center closest to it.

[0045] Furthermore, the new cluster center corresponding to each cluster can be calculated according to the current clustering situation. At the same time, the objective function can be calculated to measure the clustering effect. Then, the cluster center can be updated iteratively. After each iteration, it is necessary to check whether the change value of the objective function before and after the iteration is less than the preset iteration threshold, or whether the maximum number of iterations has been reached. If the conditions are met, the iteration is stopped, and the water quality change trend corresponding to the target water quality data is determined according to the final clustering result; if not, the new cluster center is used as the current cluster center, and the above iterative operation is repeated.

[0046] A water volume prediction model for the water system is constructed, and future flow data is predicted based on the target flow data. The corresponding calculation formula is as follows: In the formula, represents the future traffic data at time t; represents the moving average partial polynomial; q represents the moving average order, that is, the amount of white noise; represents a white noise sequence; represents the autoregressive partial polynomial; p represents the autoregressive order, that is, the number of target flow data; B represents the backshift operator; A represents the difference order.

[0047] Among them, the water volume prediction model refers to the model used to predict future flow data of the water system.

[0048] In practical applications, we can first determine the various parameters of the water volume prediction model, including the moving average order, autoregressive order, and difference order. The moving average order is the number of white noises, and the autoregressive order is the number of target flow data.

[0049] Then, the collected target flow data can be input into the water volume prediction model to obtain future flow data, and then the current flow strategy of the water system can be managed and scheduled according to the future flow conditions.

[0050] Constructing a fault prediction model for the water system and predicting the system failure probability of the water system according to the target pressure data, specifically includes: The target pressure data is input into the input layer of the fault prediction model, and the input value of the u-th node in the hidden layer of the fault prediction model is as follows: In the formula, represents the input value of the u-th node in the hidden layer of the fault prediction model; R represents the number of target pressure data in the input layer; Represents the weight of the rth target pressure data in the input layer to the uth node in the hidden layer; Represents the rth target pressure data in the input layer; represents the bias term of the u-th node in the hidden layer; The corresponding output value of the u-th node in the hidden layer is as follows: In the formula, Represents the output value of the u-th node in the hidden layer of the fault prediction model; represents the input value of the u-th node in the hidden layer of the fault prediction model; e represents a natural constant; The input values ​​of the output layer of the fault prediction model are as follows: In the formula, represents the input value of the output layer of the fault prediction model; U represents the number of nodes in the hidden layer; represents the weight from the uth node in the hidden layer to the output layer; Represents the output value of the u-th node in the hidden layer of the fault prediction model; Represents the bias term of the output layer; The corresponding output of the output layer is as follows: In the formula, Represents the output value of the output layer of the fault prediction model; represents the input value of the output layer of the fault prediction model; e represents a natural constant; The output value of the output layer is the system failure probability.

[0051] It should be noted that the fault prediction model refers to a model used to predict whether there is a fault in the water system.

[0052] In practical applications, the target pressure data can be input into the input layer of the fault prediction model, and then the input value and output value of each node in the hidden layer can be calculated. Furthermore, the input value and output value of the output layer of the fault prediction model can be calculated based on the output value of the hidden layer. The output value of the output layer is the system failure probability, which reflects the possibility of failure in the water system.

[0053] The preset alarm conditions include water quality alarm conditions, flow alarm conditions and pressure alarm conditions; When the water quality change trend meets the water quality alarm condition, the future flow data meets the flow alarm condition, or the system failure probability meets the pressure alarm condition, it is determined that the water system has a failure and the system alarm mechanism of the water system is triggered.

[0054] It is understandable that when the trend of water quality changes meets the water quality alarm conditions, it can be judged that there are water quality problems in the water system. For example, suppose the water quality alarm condition is that the lead content in the water source exceeds 0.01 mg / L. After a multi-dimensional analysis of the target water quality data, it is concluded that the trend of water quality changes is that the lead content in the current water source continues to rise, reaching 0.015 mg / L, exceeding the set water quality alarm conditions. At this point, it can be judged that there are water quality problems in the water system, and it may affect the subsequent water supply safety.

[0055] If the future flow data meets the flow alarm conditions, it can be judged that there may be abnormalities in the flow of the water system, affecting the normal operation of the system. For example, the flow alarm condition is set to the water plant's outflow flow exceeding 90% of the maximum design flow. By analyzing and predicting future flow data, it is found that the water plant's outflow flow will reach 95% of the maximum design flow in a certain period of time in the future, meeting the flow alarm conditions. At this time, it can be judged that there are abnormalities in the water system in terms of flow, which may cause excessive pressure in the water pipeline, and even the risk of pipe burst, affecting the normal operation of the system. At this time, it is necessary to adjust the water supply scheduling plan in advance, such as appropriately reducing the water supply in other areas.

[0056] When the system failure probability meets the pressure alarm condition, it can be judged that the water system may fail due to pressure problems. For example, suppose the pressure alarm condition is when the system failure probability exceeds 0.6, and the system failure probability calculated by the fault prediction model is 0.7, which meets the pressure alarm condition. Therefore, it can be judged that the water system may fail due to pressure problems, such as pipe rupture, equipment damage, etc. At this time, it is necessary to arrange maintenance personnel to inspect and maintain the pipe network and equipment in time to ensure the normal operation of the water system.

[0057] When a water system failure is detected, its alarm mechanism can be automatically triggered, and relevant personnel can be informed of the system failure through various means such as sound, light, information push, etc., and reminded to take maintenance measures in a timely manner.

[0058] Embodiment 2 like Figure 3 As shown, a multi-dimensional monitoring alarm and intelligent water management method based on the MQTT protocol includes: S1, collects data from the water system based on the sensor network and generates target water data; S2, converting the format of the target water service data based on the MQTT protocol, and transmitting the format to the MQTT server through the IoT gateway; S3, based on the MQTT server, performing a multi-dimensional analysis on the target water service data to obtain a multi-dimensional data analysis result; S4, adjusting the water management strategy of the water system in real time according to the multi-dimensional data analysis results; S5, obtaining preset alarm conditions, and performing fault monitoring on the water system according to the preset alarm conditions and the multi-dimensional data analysis results.

[0059] Through the introduction of the above embodiments, the present invention can collect data from the water system based on the sensor network and generate target water data through a multi-dimensional monitoring, alarm and intelligent water management system and method based on the MQTT protocol; convert the format of the target water data based on the MQTT protocol, and transmit it to the MQTT server through the Internet of Things gateway; based on the MQTT server, perform multi-dimensional analysis on the target water data to obtain multi-dimensional data analysis results; according to the multi-dimensional data analysis results, make real-time adjustments to the water management strategy of the water system; obtain preset alarm conditions, and perform fault monitoring on the water system according to the preset alarm conditions and multi-dimensional data analysis results, so as to utilize the advantages of the MQTT protocol, combine multi-dimensional data processing and intelligent decision-making technology, realize accurate monitoring, timely alarm and intelligent management of the water system, improve the efficiency and quality of water management, and ensure the rational use of water resources and the stable operation of the water system.

[0060] The present invention can realize comprehensive, real-time acquisition and stable transmission of water data through multi-source data collection and MQTT protocol transmission; and can perform multi-dimensional analysis of water data to provide a scientific basis for intelligent alarm and management decision-making; the system of the present invention has intelligent management decision-making functions, which can realize the optimal allocation of water resources and efficient management of equipment; in addition, the system of the present invention ensures the timely discovery and handling of abnormal situations through an intelligent alarm mechanism, thereby improving the level of refinement of water management, ensuring the safe and stable operation of the water system, and promoting the sustainable use of water resources.

[0061] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0062] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0063] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. Multi-dimensional monitoring alarm and intelligent water management system based on MQTT protocol, characterized by: The system comprises: A data collection module is used to collect data from the water system based on a sensor network and generate target water data; A conversion and transmission module, used for converting the format of the target water service data based on the MQTT protocol, and transmitting the format to the MQTT server through the Internet of Things gateway; A data analysis module, used to perform multi-dimensional analysis on the target water affairs data based on the MQTT server to obtain multi-dimensional data analysis results; A strategy adjustment module, used to adjust the water management strategy of the water system in real time according to the multi-dimensional data analysis results; The fault monitoring module is used to obtain preset alarm conditions and perform fault monitoring on the water system according to the preset alarm conditions and the multi-dimensional data analysis results.

2. The multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol according to claim 1 is characterized in that: The data acquisition module is used to collect data from the water system based on the sensor network to generate target water data, specifically including: The sensor network includes a water quality sensor, a flow sensor and a pressure sensor; Based on the water quality sensor, a water quality analog signal of the water source corresponding to the water system is collected; based on the flow sensor, a flow analog signal of the water plant corresponding to the water system is collected; based on the pressure sensor, a pressure analog signal of the water transmission and distribution network corresponding to the water system is collected; Aggregating the water quality simulation signal, the flow simulation signal and the pressure simulation signal to generate a water affairs simulation signal; Performing analog-to-digital conversion on the water affairs analog signal to obtain a water affairs digital signal, and encapsulating the water affairs digital signal to obtain the target water affairs data; The target water service data includes target water quality data, target flow data and target pressure data.

3. The multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol according to claim 2 is characterized in that: The step of performing analog-to-digital conversion on the water affairs analog signal to obtain the water affairs digital signal specifically includes: The analog-to-digital conversion reference voltage and the analog-to-digital conversion bit number are obtained, and the water service analog signal is converted into a digital form. The calculation formula of the water service digital signal is as follows: In the formula, Indicates water service digital signal; Indicates water service analog signal; represents the analog-to-digital conversion reference voltage; f represents the number of analog-to-digital conversion bits.

4. The multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol according to claim 1 is characterized in that: The conversion and transmission module is used to convert the format of the target water service data based on the MQTT protocol and transmit it to the MQTT server through the Internet of Things gateway, specifically including: Based on the MQTT protocol, the data format of the target water service data is converted into the MQTT message format, and transmitted to the MQTT server through the Internet of Things gateway, and the MQTT server is equipped with a load balancing device; A heartbeat reconnection mechanism is set in the Internet of Things gateway and the MQTT server, the Internet of Things gateway sends a heartbeat packet to the MQTT server according to the heartbeat interval, and records the heartbeat sending time when the Internet of Things gateway sends the heartbeat packet and the heartbeat receiving time when the MQTT server receives the heartbeat packet; If the heartbeat waiting time between the heartbeat sending time and the heartbeat receiving time exceeds the heartbeat timeout threshold, the heartbeat reconnection mechanism is triggered, and the Internet of Things gateway and the MQTT server are reconnected.

5. The multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol according to claim 1 or 2, characterized in that: The data analysis module is used to perform multi-dimensional analysis on the target water affairs data based on the MQTT server to obtain multi-dimensional data analysis results, specifically including: The target water quality data set is set as , represents the i-th target water quality data; n represents the number of target water quality data; Obtain a preset cluster number K, randomly select K target water quality data as cluster centers, and the data set composed of the cluster centers is , represents the hth cluster center; For the target water quality data , calculate the target water quality data To cluster center Distance as follows: In the formula, Indicates target water quality data To cluster center distance; J represents the target water quality data The characteristic dimension of Indicates target water quality data The jth feature of Represents the cluster center The jth feature of The target water quality data Assign to the nearest cluster center The corresponding cluster , and the target water quality data To the nearest cluster center The distances are as follows: In the formula, Indicates target water quality data To the nearest cluster center distance; Indicates target water quality data To cluster center The distance between the two groups is ; K represents the preset number of clusters; Calculate clusters The corresponding new cluster center as follows: In the formula, Representation clustering The corresponding new cluster center; represents the hth cluster; Representation clustering The number of target water quality data; represents the i-th target water quality data; The objective function is calculated as follows: Where, J represents the objective function; represents the i-th target water quality data; represents the hth cluster center; represents the hth cluster; K represents the preset number of clusters; Indicates target water quality data To cluster center The Euclidean distance of Iteratively update the cluster center until the change value of the objective function before and after the iteration is less than a preset iteration threshold, or the objective function reaches a maximum number of iterations, stop the iteration operation, and divide the target water quality data into different clusters, and determine the water quality change trend corresponding to the target water quality data according to the clustering result; Otherwise, the dataset composed of new cluster centers As the current cluster center, and repeat the above iterative operation.

6. The multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol according to claim 5 is characterized in that: A water volume prediction model for the water system is constructed, and future flow data is predicted based on the target flow data. The corresponding calculation formula is as follows: In the formula, represents the future traffic data at time t; represents the moving average partial polynomial; q represents the moving average order, that is, the amount of white noise; represents a white noise sequence; represents the autoregressive partial polynomial; p represents the autoregressive order, that is, the number of target flow data; B represents the backshift operator; A represents the difference order.

7. The multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol according to claim 6 is characterized in that: Constructing a fault prediction model for the water system and predicting the system failure probability of the water system according to the target pressure data, specifically comprising: The target pressure data is input into the input layer of the fault prediction model, and the input value of the u-th node in the hidden layer of the fault prediction model is as follows: In the formula, represents the input value of the u-th node in the hidden layer of the fault prediction model; R represents the number of target pressure data in the input layer; Represents the weight of the rth target pressure data in the input layer to the uth node in the hidden layer; Represents the rth target pressure data in the input layer; represents the bias term of the u-th node in the hidden layer; The corresponding output value of the u-th node in the hidden layer is as follows: In the formula, Represents the output value of the u-th node in the hidden layer of the fault prediction model; represents the input value of the u-th node in the hidden layer of the fault prediction model; e represents a natural constant; The input values ​​of the output layer of the fault prediction model are as follows: In the formula, represents the input value of the output layer of the fault prediction model; U represents the number of nodes in the hidden layer; represents the weight from the uth node in the hidden layer to the output layer; Represents the output value of the u-th node in the hidden layer of the fault prediction model; Represents the bias term of the output layer; The corresponding output of the output layer is as follows: In the formula, Represents the output value of the output layer of the fault prediction model; represents the input value of the output layer of the fault prediction model; e represents a natural constant; The output value of the output layer is the system failure probability.

8. The multi-dimensional monitoring alarm and intelligent water management system based on the MQTT protocol according to claim 7 is characterized in that: The preset alarm conditions include water quality alarm conditions, flow alarm conditions and pressure alarm conditions; When the water quality change trend meets the water quality alarm condition, the future flow data meets the flow alarm condition, or the system failure probability meets the pressure alarm condition, it is determined that the water system has a failure and the system alarm mechanism of the water system is triggered.

9. A multi-dimensional monitoring, alarm and intelligent water management method based on the MQTT protocol, applied to the multi-dimensional monitoring, alarm and intelligent water management system based on the MQTT protocol as claimed in any one of claims 1 to 8, the method comprising: Collect data from the water system based on the sensor network to generate target water data; The target water service data is formatted based on the MQTT protocol and transmitted to the MQTT server through the IoT gateway; Based on the MQTT server, a multi-dimensional analysis is performed on the target water service data to obtain a multi-dimensional data analysis result; According to the multi-dimensional data analysis results, the water management strategy of the water system is adjusted in real time; Acquire preset alarm conditions, and perform fault monitoring on the water system according to the preset alarm conditions and the multi-dimensional data analysis results.

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