Mobile terminal-based remote monitoring and alarm handling system and method for sewage treatment plant
By using a mobile terminal-based remote monitoring system for wastewater treatment plants, combined with trend prediction and intelligent analysis models, the system addresses the issues of insufficient remote access and reliance on manual alarms in existing systems. It enables real-time, intelligent remote monitoring and alarm handling, thereby improving the management level of wastewater treatment plants.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-19
- Publication Date
- 2026-06-12
Smart Images
Figure CN122200915A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to remote monitoring and alarm handling of wastewater treatment plants, specifically providing a system and method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals. Background Technology
[0002] Currently, wastewater treatment plants commonly employ automated control systems centered around PLCs and supervisory control computers (SCADA) to monitor and control equipment such as pumps, fans, and valves, as well as process parameters like pH, dissolved oxygen, and COD. These systems primarily rely on on-site monitoring computers for data acquisition, storage, and visualization, and achieve centralized management through SCADA systems. However, existing systems often store data on local servers, limiting remote access capabilities and making it difficult for managers to obtain equipment operating status and process parameters from outside the plant in a timely manner. Furthermore, traditional systems have limitations in data transmission and multi-terminal access, failing to meet the real-time monitoring and remote management needs of modern wastewater treatment plants.
[0003] Furthermore, existing wastewater treatment plant monitoring systems often rely on fixed thresholds for alarm mechanisms, lacking predictive analysis of equipment operating status and process parameter trends, which can easily lead to false alarms or missed alarms. Alarm handling depends on manual experience, resulting in slow response times and insufficient standardization and intelligence. Simultaneously, traditional systems lack multi-level alarm hierarchical management, alarm list management, and automatic handling functions, and are difficult to deeply integrate with mobile terminals and cloud databases, limiting the improvement of remote monitoring, early warning, and automated management capabilities.
[0004] Therefore, there is an urgent need in this field for a remote monitoring and alarm handling system and method for wastewater treatment plants based on mobile terminals to solve the above problems. Summary of the Invention
[0005] The present invention aims to solve the above-mentioned technical problems, namely, to solve the problems of insufficient remote access capability, easy false alarms or missed alarms, and low level of intelligence in alarm handling due to reliance on manual labor.
[0006] In a first aspect, the present invention provides a remote monitoring and alarm handling system for wastewater treatment plants based on mobile terminals. The system includes an equipment layer, a control layer, a transmission layer, a monitoring layer, a data interface module, a cloud database, and a mobile terminal. The equipment layer is used to acquire the equipment operating status parameters and process parameters of the wastewater treatment plant, and the equipment layer also includes actuators; The device layer is connected to the control layer via a signal, and the control layer is used to process the device operating status parameters and process parameters acquired by the device layer. Both the control layer and the monitoring layer are signal-connected to the transmission layer, and the transmission layer is used to realize bidirectional transmission between the control layer and the monitoring layer; The monitoring layer is used to store and display the equipment operating status parameters and the process parameters. The monitoring layer can generate alarm information based on the equipment operating status parameters and the process parameters. The monitoring layer is also used to receive control commands, which are used to control the actuators. Both the monitoring layer and the cloud database are signal-connected to the data docking module. The data docking module is used to transmit the equipment operating status parameters, the process parameters, and the alarm information to the cloud database. The cloud database is used to store the equipment operating status parameters, the process parameters, and the alarm information; The mobile terminal is connected to the cloud database, and the mobile terminal is used to display the equipment operating status parameters, the process parameters, and the alarm information.
[0007] In a second aspect, the present invention provides a method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals. The method is used in the aforementioned remote monitoring and alarm handling system for wastewater treatment plants based on mobile terminals, and includes the following steps: Determine whether to issue an alarm based on the equipment's operating status parameters and process parameters.
[0008] In a specific implementation of the above-mentioned method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals, "determining whether to issue an alarm based on equipment operating status parameters and process parameters" includes the following steps: If the equipment operating status parameters or the process parameters reach a preset threshold, an alarm will be issued; Based on the equipment operating status parameters and the process parameters, the trend prediction values of the equipment operating status parameters and the process parameters are determined. If the trend prediction value of the equipment operating status parameters or the trend prediction value of the process parameters reaches a preset threshold, an alarm is issued.
[0009] In a specific embodiment of the above-mentioned method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals, "determining the trend prediction values of the equipment operating status parameters and the process parameters based on the equipment operating status parameters and the process parameters" includes the following steps: A training dataset is constructed based on the historical records of equipment operating status parameters and water treatment process parameters in the cloud database. A time-based feature library of parameter changes is established based on the training dataset; Based on the parameter change feature library, a trend prediction model is trained using a time series prediction algorithm; The equipment operating status parameters and the process parameters are input into the trend prediction model, which can output the trend prediction values of the equipment operating status parameters and the process parameters.
[0010] In a specific embodiment of the above-mentioned method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals, the method further includes the following steps: Determine the alarm action based on the alarm level.
[0011] In a specific embodiment of the above-mentioned method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals, the method further includes the following steps: An automatic handling plan will be determined based on the alarm.
[0012] In a specific embodiment of the above-mentioned method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals, "determining the handling plan based on the alarm" includes the following steps: An experience dataset was created based on the operational records of technical personnel. Based on the aforementioned experience dataset, a machine learning algorithm is used to train an intelligent judgment model; When an alarm is issued, the current equipment operating status parameters and process parameters are input into the intelligent judgment model, and the intelligent judgment model can output the automatic handling plan.
[0013] By adopting the above technical solution, the present invention can realize the real-time acquisition, processing and display of the operating status and process parameters of wastewater treatment plant equipment. Through the data docking module and cloud database, the monitoring information is transmitted to the mobile terminal to realize remote monitoring outside the plant area. At the same time, the system can automatically generate alarm information based on the equipment operating status and process parameters, support multi-level alarm management, and directly drive the actuators to perform response operations through control commands, thereby improving the real-time performance, accuracy and intelligence level of monitoring, and achieving the technical effect of remote early warning and automatic handling.
[0014] Furthermore, this invention can determine whether to issue an alarm in real time based on equipment operating status parameters and process parameters, and combine a trend prediction model to analyze the future change trends of key parameters, thereby achieving early warning of potential anomalies. By constructing a historical dataset and a parameter change feature library, and using a time series prediction algorithm to train the trend prediction model, the system can accurately predict the change trends of equipment operating status and process indicators, thereby improving the accuracy and foresight of alarms and enhancing the intelligent level of remote monitoring and early warning response in wastewater treatment plants.
[0015] Furthermore, this invention can automatically determine the corresponding alarm measures according to the alarm level, realize hierarchical management of low, medium and high risk levels, and transmit alarm information to relevant personnel in a timely manner through multiple channels, thereby improving the timeliness and pertinence of alarm response and enhancing the intelligence and refinement of remote monitoring and safety management of wastewater treatment plants.
[0016] Furthermore, this invention can construct an experience dataset based on historical operation records and train an intelligent judgment model through machine learning to achieve automatic analysis and handling of alarms. When an alarm occurs, the system inputs the real-time equipment operating status and process parameters into the intelligent judgment model, automatically generates the corresponding handling plan, and can directly execute it, thereby improving the speed, accuracy, and automation level of alarm response and significantly enhancing the intelligent capabilities of remote monitoring and operation and maintenance management of wastewater treatment plants. Attached Figure Description
[0017] The preferred embodiments of the present invention are described below with reference to the accompanying drawings, in which: Figure 1 This is a schematic diagram of the structure of a remote monitoring and alarm handling system for wastewater treatment plants based on a mobile terminal, provided by the present invention. Detailed Implementation
[0018] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.
[0019] It should be noted that in the description of this invention, terms such as "upper," "lower," "left," "right," "inner," and "outer," indicating directional or positional relationships, are based on the directional or positional relationships shown in the accompanying drawings. These are merely for ease of description and do not indicate or imply that the device or element 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. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.
[0020] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "setting," and "connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection, an indirect connection through an intermediate medium, or a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.
[0021] To address the issues of insufficient remote access capabilities, frequent false alarms or missed alarms, and reliance on manual alarm handling with low levels of intelligence in wastewater treatment plant monitoring systems, this embodiment discloses a remote monitoring and alarm handling system for wastewater treatment plants based on mobile terminals. This system includes an equipment layer, a control layer, a transmission layer, a monitoring layer, a data interface module, a cloud database, and a mobile terminal. See details below. Figure 1 .
[0022] The equipment layer includes equipment status monitoring devices, water treatment process monitoring devices, and actuators. Equipment status monitoring devices monitor the operating status of equipment such as pumps, fans, and bar screens. Operating status parameters include start / stop, running, and standby status, as well as fault signals such as overload, short circuit, and abnormal shutdown. Equipment status monitoring devices output digital signals, specifically 24V DC signals. Water treatment process monitoring devices monitor water treatment process parameters. These include pH meters, dissolved oxygen sensors, sludge concentration sensors, online COD monitors, flow meters, and level gauges. Water treatment process monitoring devices output analog signals, specifically 4mA to 20mA analog signals, or 0V to 10V analog signals. Actuators include electric valves and frequency converters. Actuators can output their own operating status, such as valve opening degree and frequency converter frequency. Actuators can also execute actions corresponding to control commands.
[0023] The control layer receives signals output from the device layer, processes these signals, performs data processing and logical operations, and then sends the processed data to the monitoring layer. The control layer also receives control commands from the monitoring layer and transmits them to the actuators. The control layer includes digital input modules, analog input modules, a main controller, and a communication module. The digital input modules, also known as DI modules, receive digital signals output from the device layer. The analog input modules, also known as AI modules, receive analog signals output from the device layer. The main controller, specifically a PLC, performs logical operations and data processing on the signals input from the device layer and executes preset control logic. The communication module sends data output from the main controller to the transmission layer and receives control commands from the monitoring layer. Specifically, the communication module supports mainstream industrial communication protocols such as Modbus and Profinet, with a data transmission delay of no more than 10ms.
[0024] The transport layer enables bidirectional data transmission between the control and monitoring layers, ensuring stable data transmission, resistance to interference, and prevention of data loss or distortion. The transport layer includes industrial switches and industrial Ethernet. Industrial switches are used for data routing and signal amplification. Specifically, industrial-grade gigabit switches are selected, supporting multi-port access and simultaneously connecting communication modules of the control layer, the monitoring layer, and other network devices to achieve efficient data routing. Furthermore, industrial switches possess anti-interference and high / low temperature resistance characteristics, making them suitable for industrial environments such as wastewater treatment plants and preventing signal attenuation during transmission. Industrial Ethernet is the core transmission medium, replacing traditional ordinary cables, offering advantages such as high transmission speed, strong anti-interference capability, and long transmission distance. Industrial Ethernet is responsible for stably transmitting data forwarded by the control layer to the monitoring layer, while simultaneously transmitting control commands from the monitoring layer back to the control layer, ensuring smooth bidirectional transmission.
[0025] The monitoring layer stores and displays equipment operating status parameters and process parameters. It generates alarm information based on these parameters. The monitoring layer also receives control commands, which are used to control actuators. It receives equipment operating parameters and process parameters through the transmission layer to achieve data storage, parameter visualization, and report generation. The monitoring layer also provides a control interface for operators to issue control commands. Specifically, the monitoring layer includes a host computer with a SCADA configuration system. This system includes software such as WinCC, KingSCADA, and Intouch, which displays real-time operating status parameters and process parameters of the field equipment through simulated screens, such as pump start / stop status, pH value, and flow rate. The monitoring layer also includes supporting functional modules, such as industrial databases like SQL Server and MySQL, for storing equipment operating status parameters, process parameters, and alarm information. The storage period is no less than one year, and historical data traceability is supported. These supporting functional modules can also automatically generate daily, weekly, and monthly operation reports, including parameter statistics and equipment operating status, meeting the needs of technical solution archiving, environmental supervision, and internal management. Furthermore, the monitoring layer supports manual / automatic control switching. Operators can view the entire process operation and issue control commands, such as equipment start / stop and parameter adjustment, through the host computer on the monitoring layer. The supporting functional modules also have anomaly alarm functions, automatically issuing audible and visual alerts when parameters exceed limits or equipment malfunctions, so that operators can take timely action.
[0026] Both the monitoring layer and the cloud database are connected to a data interface module. This module transmits equipment operating status parameters, process parameters, and alarm information to the cloud database. The data interface module uses the Modbus / Profinet industrial communication protocol to obtain equipment operating status parameters, process indicators, and alarm information from the host computer. The data acquisition frequency of the data interface module is synchronized with the host computer's acquisition frequency, for example, acquiring data every 1 to 5 seconds to ensure real-time data accuracy.
[0027] The cloud database is used to store equipment operating status parameters, process parameters, and alarm information. Specifically, an industrial-grade cloud database is selected to build a data storage server, which receives data uploaded by the data interface module to achieve real-time data storage and historical data archiving, with a storage period of no less than one year. This setup supports fast data querying and retrieval, and also has data backup capabilities to prevent data loss.
[0028] The mobile terminal is specifically a WeChat mini-program. The mobile terminal connects to a cloud database to display equipment operating status parameters, process parameters, and alarm information. Managers can view equipment operating status parameters, process parameters, historical data, alarm records, etc., through the mobile terminal to achieve real-time monitoring outside the plant area.
[0029] In summary, the system operates as follows: Signals collected at the device layer are transmitted to the digital and analog input modules at the control layer. These modules convert the signals and transmit them to the main controller, which then processes the data and performs logical operations. The main controller transmits the processed data via a communication module to an industrial switch at the transmission layer, and then reliably to the monitoring layer via an industrial Ethernet network. Upon receiving the data, the monitoring layer performs visualization and data storage. Operators can issue control commands based on the monitoring data. These commands are transmitted back through the transmission and control layers to the actuators at the device layer to execute the corresponding operations.
[0030] This embodiment also includes a method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals, the method comprising the following steps: Determine whether to issue an alarm based on the equipment's operating status parameters and process parameters.
[0031] This step specifically includes the following steps: If the device's operating status parameters reach a preset threshold, an alarm will be issued; If the process parameters reach the preset threshold, an alarm will be issued; If the trend prediction value of the equipment operating status parameter reaches the preset threshold, an alarm will be issued; An alarm will be issued if the trend prediction value of the process parameters reaches the preset threshold.
[0032] The trend prediction values of equipment operating status parameters and process parameters are obtained through a trend prediction model. The specific training method for the trend prediction model includes the following steps: S11. Construct a training dataset based on historical records of equipment operating status parameters and water treatment process parameters from the cloud database. Specifically, extract historical records of equipment operating status parameters and water treatment process parameters from the cloud database and preprocess the historical data. Preprocessing includes data cleaning, data denoising, effective data filtering, and trend analysis. Data cleaning removes outliers, missing values, and duplicate data; data denoising uses smoothing filtering or moving average algorithms to reduce noise interference; effective data filtering retains complete periodic data and valid operating condition data; trend analysis performs time-dimensional analysis on key parameters to extract their daily and weekly variation patterns.
[0033] S12. Establish a time-based parameter change feature library based on the training dataset. This library records the change characteristics of each monitoring parameter over different time periods. These characteristics include, but are not limited to: daily trends in dissolved oxygen (DO), daily trends in chemical oxygen demand (COD), the coupling relationship between DO and COD, and the correlation between equipment operating parameters and process indicators. This parameter change feature library serves as the foundation dataset for training subsequent trend prediction models.
[0034] S13. Using a parameter change feature library, a trend prediction model is trained using time series forecasting algorithms. Specifically, the time series forecasting algorithms include the Long Short-Term Memory (LSTM) neural network algorithm and the Autoregressive Moving Average (ARIMA) model algorithm. The specific training process includes: segmenting historical data in the parameter change feature library according to time series to construct training and validation sets; inputting the historical time series of monitoring parameters into the prediction model for training; using the model to learn the parameter change patterns and establishing a prediction function; and calibrating the model to improve prediction accuracy. After training, a trend prediction model is obtained. This trend prediction model can receive real-time monitoring point values as input and predict the changing trends of equipment operating status and process indicators within the next 1 to 24 hours.
[0035] S14. Input the equipment operating status parameters and process parameters into the trend prediction model. The trend prediction model can output the trend prediction values of the equipment operating status parameters and the trend prediction values of the process parameters.
[0036] The method also includes the following steps: Determine the alarm measures based on the alarm level.
[0037] In this embodiment, alarms are categorized into low-risk, medium-risk, and high-risk. Low-risk alarms are pushed via WeChat. Medium-risk alarms are pushed via WeChat and SMS. High-risk alarms are pushed via WeChat, SMS, and by automatically playing an alarm voice message during a phone call. Furthermore, corresponding alarm lists are established for different levels and types of alarms.
[0038] The method also includes the following steps: Determine the automatic handling plan based on the alarm.
[0039] This step specifically includes the following steps: When an alarm is issued, the equipment operating status parameters and process parameters at that time are input into the intelligent judgment model, and the intelligent judgment model can output an automatic handling plan. The control commands generated by the automatic handling scheme are transmitted to the corresponding actuators through the control layer, so that the actuators can perform the corresponding actions.
[0040] The training method for the intelligent judgment model includes the following steps: S21. Establish an experience dataset based on the operational records of technical personnel. Specifically, collect the operational experience of wastewater treatment technicians in equipment operation and process management, including parameter adjustment schemes for different alarm types and scenarios. Organize the collected data into a standardized dataset, and combine it with historical alarm data and parameter adjustment records in the cloud database to form a comprehensive dataset required for training the intelligent judgment model, providing sufficient training samples and reference for the model.
[0041] S22, based on an experience dataset, employs machine learning algorithms to train an intelligent judgment model. It collects operational experience from wastewater treatment technicians in equipment operation and process management, including parameter adjustment schemes for different alarm types and scenarios. The collected data is organized into a standardized dataset and combined with historical alarm data and parameter adjustment records from a cloud database to form a comprehensive dataset required for training the intelligent judgment model, providing sufficient training samples and reference for the model.
[0042] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.
Claims
1. A remote monitoring and alarm handling system for wastewater treatment plants based on mobile terminals, characterized in that, It includes the device layer, control layer, transmission layer, monitoring layer, data interface module, cloud database, and mobile terminal; The equipment layer is used to acquire the equipment operating status parameters and process parameters of the wastewater treatment plant, and the equipment layer also includes actuators; The device layer is connected to the control layer via a signal, and the control layer is used to process the device operating status parameters and process parameters acquired by the device layer. Both the control layer and the monitoring layer are signal-connected to the transmission layer, and the transmission layer is used to realize bidirectional transmission between the control layer and the monitoring layer; The monitoring layer is used to store and display the equipment operating status parameters and the process parameters. The monitoring layer can generate alarm information based on the equipment operating status parameters and the process parameters. The monitoring layer is also used to receive control commands, which are used to control the actuators. Both the monitoring layer and the cloud database are signal-connected to the data docking module. The data docking module is used to transmit the equipment operating status parameters, the process parameters, and the alarm information to the cloud database. The cloud database is used to store the equipment operating status parameters, the process parameters, and the alarm information; The mobile terminal is connected to the cloud database, and the mobile terminal is used to display the equipment operating status parameters, the process parameters, and the alarm information.
2. A method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals, characterized in that, The method is used in the remote monitoring and alarm handling system for wastewater treatment plants based on mobile terminals as described in claim 1, and the method includes the following steps: Determine whether to issue an alarm based on the equipment's operating status parameters and process parameters.
3. The method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals according to claim 2, characterized in that, "Determining whether to issue an alarm based on equipment operating status parameters and process parameters" includes the following steps: If the equipment operating status parameters or the process parameters reach a preset threshold, an alarm will be issued; Based on the equipment operating status parameters and the process parameters, the trend prediction values of the equipment operating status parameters and the process parameters are determined. If the trend prediction value of the equipment operating status parameters or the trend prediction value of the process parameters reaches a preset threshold, an alarm is issued.
4. The method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals according to claim 3, characterized in that, "Determining the trend prediction values of the equipment operating status parameters and the process parameters based on the equipment operating status parameters and the process parameters" includes the following steps: A training dataset is constructed based on the historical records of equipment operating status parameters and water treatment process parameters in the cloud database. A time-based feature library of parameter changes is established based on the training dataset; Based on the parameter change feature library, a trend prediction model is trained using a time series prediction algorithm; The equipment operating status parameters and the process parameters are input into the trend prediction model, which can output the trend prediction values of the equipment operating status parameters and the process parameters.
5. The method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals according to claim 3, characterized in that, The method further includes the following steps: Determine the alarm action based on the alarm level.
6. The method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals according to claim 3, characterized in that, The method further includes the following steps: An automatic handling plan will be determined based on the alarm.
7. The method for remote monitoring and alarm handling of wastewater treatment plants based on mobile terminals according to claim 6, characterized in that, "Determining a handling plan based on the alarm" includes the following steps: An experience dataset was created based on the operational records of technical personnel. Based on the aforementioned experience dataset, a machine learning algorithm is used to train an intelligent judgment model; When an alarm is issued, the current equipment operating status parameters and process parameters are input into the intelligent judgment model, and the intelligent judgment model can output the automatic handling plan.