Intelligent dosing device for wastewater treatment
By generating dosing strategies through a distributed multi-parameter sensor array and intelligent analysis unit, combined with high-precision actuators and remote monitoring, the problems of single detection parameters and rigid control strategies in traditional dosing devices are solved, achieving efficient, precise and intelligent wastewater treatment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- BEIJING JINGRUN WATER CO LTD
- Filing Date
- 2025-07-02
- Publication Date
- 2026-06-09
AI Technical Summary
Existing wastewater treatment dosing devices suffer from limited detection parameters, rigid control strategies, and insufficient execution precision, leading to either overdosing or underdosing, resulting in low treatment efficiency, reagent waste, and a high risk of secondary pollution. Furthermore, they lack remote monitoring and adaptive optimization capabilities.
It employs a distributed multi-parameter sensor array, intelligent analysis unit, dynamic dosing control module, and feedback adjustment module, combined with a multi-parameter detection module, to generate a dosing strategy through multi-parameter coupling analysis. It utilizes a high-precision metering pump and electromagnetic regulating valve to achieve precise dosing, and combines anti-crystallization design with a remote monitoring terminal to achieve intelligent decision-making and adaptive optimization.
It has achieved high efficiency, precision and intelligence in wastewater treatment, increased the utilization rate of reagents by more than 40%, and achieved a wastewater compliance rate of over 99%, reducing reliance on manual intervention and the risk of system fault tolerance.
Smart Images
Figure CN224337264U_ABST
Abstract
Description
Technical Field
[0001] This utility model provides a dosing device, belonging to the technical field of intelligent wastewater treatment system equipment, and particularly relates to a dosing device for intelligent wastewater treatment. Background Technology
[0002] Existing wastewater treatment dosing devices typically control reagent dosage based on a single parameter detection (such as pH or turbidity). Their basic structure includes a sensor unit, a control unit, and a dosing actuator. The sensor unit usually employs a single type of sensor with fixed locations. The control unit generates dosing commands through preset thresholds or simple PID algorithms. The dosing actuator relies on single-channel or dual-channel conventional metering pumps for reagent delivery. While these devices can perform basic dosing functions, they are limited by the single detection parameter, rigid control logic, and insufficient execution accuracy. They struggle to handle complex and variable wastewater compositions and highly nonlinear reaction processes, easily leading to over- or under-dosing, resulting in low treatment efficiency, reagent waste, and the risk of secondary pollution.
[0003] Furthermore, existing devices suffer from the following shortcomings: First, the sensor layout does not consider the flow field distribution and parameter spatial heterogeneity within the wastewater tank, resulting in poor representativeness of the detection data; second, the control algorithm lacks multi-parameter coupling analysis capabilities, making it impossible to dynamically adjust the combination strategy of dosing type and dosage; third, the number of dosing channels and the precision of the actuators are insufficient to meet the requirements of refined control; fourth, the reagent storage system is prone to pipe blockage due to crystallization or precipitation, and lacks automatic replenishment functionality; fifth, remote monitoring and adaptive optimization capabilities are lacking, leading to excessive reliance on manual intervention. These problems severely restrict the level of intelligence and resource utilization efficiency in wastewater treatment, necessitating an integrated dosing device capable of multi-parameter collaborative sensing, intelligent decision-making, and precise execution. Utility Model Content
[0004] In order to solve the above problems, this application provides an intelligent wastewater treatment dosing device, which solves the shortcomings of traditional devices such as single detection parameters, rigid control strategies, and insufficient execution accuracy.
[0005] To solve the above-mentioned technical problems, this utility model provides the following technical solution: a dosing device for intelligent wastewater treatment, comprising:
[0006] The multi-parameter detection module includes a distributed array of gas concentration sensors, a group of liquid concentration sensors, and a pressure sensing unit arranged in the wastewater treatment tank.
[0007] The intelligent analysis unit is communicatively connected to the multi-parameter detection module and has a built-in dosing decision algorithm model based on multi-parameter coupling analysis.
[0008] The dynamic dosing control module includes at least three independent dosing channels connected to the drug storage container, and each dosing channel is equipped with an adjustable metering device;
[0009] The feedback adjustment module receives control commands output by the intelligent analysis unit in real time and generates dynamic adjustment signals. The adjustment signals include at least a combination of parameters of drug type, drug rate and drug timing.
[0010] Preferably, the gas concentration sensor array of the multi-parameter detection module includes pH sensors, dissolved oxygen sensors, and volatile organic compound sensors arranged in layers along the depth direction of the treatment tank, and the liquid concentration sensor group includes turbidity sensors, conductivity sensors, and ion-selective electrodes arranged in different zones of the tank.
[0011] Preferably, the intelligent analysis unit includes an abnormal working condition identification submodule based on a neural network and a dosing prediction submodule based on a fuzzy control algorithm. The two submodules achieve collaborative decision-making through a data fusion processor.
[0012] Preferably, each dosing channel of the module is equipped with a high-precision metering pump and an electromagnetic regulating valve, wherein the flow resolution of the metering pump reaches 0.1 mL / min and the response time of the electromagnetic regulating valve is less than 50 ms.
[0013] Preferably, the feedback adjustment module establishes a closed-loop control system that includes a feedforward-feedback composite control mechanism. By comparing the deviation between the actual treatment effect and the preset index in real time, the weight parameters of the dosing decision algorithm model are dynamically corrected.
[0014] Preferably, it also includes a remote monitoring terminal, which is connected to the intelligent analysis unit via a wireless communication module and integrates an abnormal alarm unit, a data visualization interface, and a manual intervention interface.
[0015] Preferably, the drug storage container adopts an anti-crystallization design, is equipped with an ultrasonic oscillator and a balance monitoring sensor inside, and is connected to an automatic drug replenishment pipeline system externally.
[0016] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:
[0017] A smart wastewater treatment dosing device uses a distributed array of gas concentration sensors (including pH, dissolved oxygen, and VOCs sensors), a liquid concentration sensor group (including turbidity, conductivity, and ion-selective electrodes), and a pressure sensing unit to collect multi-dimensional environmental parameters in real time. An intelligent analysis unit, based on a neural network anomaly detection submodule and a fuzzy control algorithm submodule, performs coupled analysis on the multi-source heterogeneous data to generate dynamic combination commands including dosing type, rate, and timing. It relies on a high-precision metering pump (flow resolution 0.1 mL / min) with at least three independent dosing channels and an ultra-fast response electromagnetic regulating valve (response time < 5 seconds). The system executes dosing actions precisely within 0ms, while simultaneously comparing the treatment effect with the preset indicators in real time through a feedforward-feedback composite closed-loop control system. This dynamically adjusts the weight parameters of the decision model to optimize the dosing strategy. Combined with a chemical storage container with an anti-crystallization design (built-in ultrasonic oscillator and residual monitoring sensor) and an automatic replenishment pipeline system, the system ensures a stable supply of chemicals. Furthermore, a remote monitoring terminal connected via a wireless communication module enables data visualization, anomaly alarms, and manual intervention. Finally, through multi-module spatiotemporal coordination and matching of the fluid characteristics of the treatment tank, the system ensures the dynamic consistency between detection data and dosing actions, achieving efficient, precise, and intelligent wastewater treatment.
[0018] Other advantages, objectives and features of this invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be taught from the practice of this invention. Attached Figure Description
[0019] Figure 1 This is a system architecture diagram of a dosing device for intelligent wastewater treatment according to the present invention;
[0020] Figure 2 This is a sequence diagram of the working process of a chemical dosing device for intelligent wastewater treatment according to this utility model.
[0021] Figure 3 This is a schematic diagram of the sensor array of a dosing device for intelligent wastewater treatment according to this utility model;
[0022] Figure 4 This is a mind map of a dosing device for intelligent wastewater treatment according to the present invention. Detailed Implementation
[0023] The technical solutions of the present utility model will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present utility model, and not all embodiments. Based on the embodiments of the present utility model, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of the present utility model.
[0024] It should be noted that the terms "vertical," "horizontal," "up," "down," "left," "right," and similar expressions used in this article are for illustrative purposes only and do not represent the only possible implementation.
[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used herein in the description of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention; the term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.
[0026] like Figure 1 and Figure 2 As shown, an intelligent wastewater treatment dosing device is characterized by: real-time acquisition of gas concentration, liquid concentration, and pressure data in the wastewater treatment tank through a multi-parameter detection module, wherein a gas concentration sensor array is arranged in layers along the depth of the tank, including pH sensors, dissolved oxygen sensors, and VOCs sensors, and a liquid concentration sensor group including a turbidity sensor, a conductivity sensor, and an ion-selective electrode; based on the neural network anomaly recognition submodule and fuzzy control algorithm submodule built into the intelligent analysis unit, collaborative decision analysis is performed on the multi-parameter coupled data to generate control commands including dosing type, rate, and timing combination parameters; a dynamic dosing control module executes the dosing action through high-precision metering pumps with at least three independent dosing channels and electromagnetic regulating valves with a response time of <50ms, while a feedback regulation module constructs a feedforward-feedback composite closed-loop control system to dynamically optimize the weight parameters of the dosing decision model in real time.
[0027] In this implementation scheme, the multi-parameter detection module, through a layered sensor array and a combination of multiple types of sensors, overcomes the limitations of traditional single-point, single-parameter detection, effectively sensing the spatial heterogeneity of parameters at different depths and zones of the pool (such as dissolved oxygen gradient distribution and VOCs concentration stratification), significantly improving the comprehensiveness and representativeness of data acquisition. The intelligent analysis unit, through a neural network anomaly identification submodule (based on an LSTM network), captures the abrupt changes in wastewater composition in real time, and combines it with a fuzzy control algorithm submodule (with a dynamic adjustment mechanism for membership functions) to analyze the nonlinear relationships of multiple parameters, generating a dynamic dosing strategy adapted to complex operating conditions, completely solving the problem of poor adaptability of traditional PID control to multi-variable coupled scenarios. The dynamic dosing control module adopts a multi-channel independent control architecture (at least three dosing channels) and high-precision actuators (metering pumps with a flow resolution of 0.1 mL / min and a response time of <50 ms). The system utilizes a solenoid valve to achieve millisecond-level precise control of drug type, dosage, and dosing sequence. Compared to existing single / dual-channel systems, the dosing range is expanded by over 300%, and the response speed is increased by 4 times. The feedback adjustment module employs a feedforward-feedback composite control mechanism, using real-time processing data to reverse-correct the decision model parameter weights, forming a self-learning optimization closed loop to overcome the cumulative error problem caused by environmental disturbances in traditional open-loop control. The anti-crystallization-designed drug storage container (with a built-in ultrasonic oscillator to suppress crystal precipitation and a residual monitoring sensor triggering automatic replenishment) works in conjunction with redundant pressure sensing units to eliminate the risk of blockage in the drug delivery pipeline, ensuring continuous and stable system operation. The remote monitoring terminal integrates data visualization, anomaly alarms, and manual intervention functions through a wireless communication module, constructing a dual-mode operation system of "intelligent decision-making as the main approach and manual supervision as a supplement," reducing reliance on manual intervention while ensuring system fault tolerance. Through spatiotemporal coordination and matching of the treatment pool's fluid dynamics characteristics, the modules ultimately achieve global optimization of detection accuracy, decision-making efficiency, and execution accuracy, increasing drug utilization by over 40% and achieving a wastewater treatment compliance rate exceeding 99%.
[0028] like Figure 3 and Figure 4As shown, an intelligent wastewater treatment dosing device is characterized by: real-time acquisition of gas concentration, liquid concentration, and pressure data in the wastewater treatment tank through a multi-parameter detection module, wherein a gas concentration sensor array is arranged in layers along the depth of the tank, including pH sensors, dissolved oxygen sensors, and VOCs sensors, and a liquid concentration sensor group including a turbidity sensor, a conductivity sensor, and an ion-selective electrode; based on the neural network anomaly recognition submodule and fuzzy control algorithm submodule built into the intelligent analysis unit, collaborative decision analysis is performed on the multi-parameter coupled data to generate control commands including dosing type, rate, and timing combination parameters; a dynamic dosing control module executes the dosing action through high-precision metering pumps with at least three independent dosing channels and electromagnetic regulating valves with a response time of <50ms, while a feedback regulation module constructs a feedforward-feedback composite closed-loop control system to dynamically optimize the weight parameters of the dosing decision model in real time.
[0029] In this embodiment, the device is installed as follows: the gas sensor array of the multi-parameter detection module is fixed in layers at 0.5m intervals along the vertical direction of the treatment tank using adjustable brackets; the liquid sensor group is installed in a grid pattern at preset interfaces on the bottom and side walls of the tank; the pressure sensing unit is integrated into key nodes of the dosing pipeline; the intelligent analysis unit uses an industrial-grade embedded controller (model STM32H743) deployed in a waterproof control box, connected to the sensor group via an RS485 bus and parsing Modbus protocol data packets in real time; the independent dosing channel of the dynamic dosing control module is connected to the reagent storage container via a flange interface; the flow parameters of the high-precision metering pump (model Cole-Parmer EW-07554-20) are preset via an HMI touch screen; and the electromagnetic regulating valve (model ASCO) is... The opening and closing logic of 238) is controlled by PLC programming; the feedback adjustment module receives real-time monitoring data from a third-party water quality analyzer (such as a Hach COD online detector) through a 4-20mA analog input interface, and dynamically compares it with preset thresholds (COD≤50mg / L, ammonia nitrogen≤15mg / L). The deviation is calculated by PID to generate a weight correction coefficient; the ultrasonic oscillator (frequency 28kHz) of the drug storage container runs periodically in pulse mode. After the balance monitoring sensor (model TEConnectivity 1620-015D) triggers a low liquid level alarm, the automatic replenishment pipeline replenishes the drug from the external storage tank through a pneumatic diaphragm pump (model Yamada NDP-15); the remote monitoring terminal builds a human-machine interface based on the Web configuration platform (KingSCADA 7.5), and communicates with the field equipment through a 4G wireless module (model Huawei ME909s-821). Operators can view the three-dimensional dynamic process flow diagram, historical data curves and alarm logs in real time through a browser, and manually switch the control mode through the virtual operation panel in emergency situations. The device operates as follows: the sensor group collects environmental parameters every 10 seconds and uploads them to the intelligent analysis unit. The neural network submodule (deployed using the TensorFlow Lite framework) extracts features from the input data and outputs anomaly probability values. When the probability value exceeds 0.85, the fuzzy control algorithm submodule (the membership function library contains templates for 5 wastewater types) is triggered to perform multi-objective optimization calculations and generate a dosing instruction set (such as "PAC 120mL / min is added to channel 1 for 90s, NaOH 80mL / min is added to channel 2, and sodium hypochlorite 40mL / min is added to channel 3 alternately"). The dynamic dosing control module synchronously drives the actuators of each channel. At the same time, the feedback adjustment module calls the water quality analyzer data every 5 minutes and updates the weights of the fully connected layers of the neural network model through the gradient descent algorithm to achieve closed-loop self-optimization.In existing technologies, sensors in traditional dosing devices are typically fixed at a single point on the edge of the tank (e.g., 30cm from the liquid surface), and the control logic relies on a preset static threshold table (e.g., activating a single dosing channel when pH < 6.5). The actuator can only achieve a flow control accuracy of ±5%. In contrast, this solution reduces the dosing error rate in complex wastewater scenarios from 15%-20% in traditional solutions to less than 2% through spatially distributed detection, multi-algorithm fusion decision-making, and millisecond-level precise execution. Furthermore, the types of chemicals that can be added can be dynamically expanded according to real-time operating conditions, significantly improving system adaptability and resource utilization.
[0030] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be determined by the claims.
Claims
1. A dosing device for intelligent wastewater treatment, characterized in that, include: The multi-parameter detection module includes a distributed array of gas concentration sensors, a group of liquid concentration sensors, and a pressure sensing unit arranged in the wastewater treatment tank. The intelligent analysis unit is communicatively connected to the multi-parameter detection module and has a built-in dosing decision algorithm model based on multi-parameter coupling analysis. The dynamic dosing control module includes at least three independent dosing channels connected to the drug storage container, and each dosing channel is equipped with an adjustable metering device; The feedback adjustment module receives control commands output by the intelligent analysis unit in real time and generates dynamic adjustment signals. The adjustment signals include at least a combination of parameters of drug type, drug rate and drug timing.
2. The intelligent wastewater treatment dosing device according to claim 1, characterized in that: The gas concentration sensor array of the multi-parameter detection module includes pH sensors, dissolved oxygen sensors, and volatile organic compound sensors arranged in layers along the depth direction of the treatment tank. The liquid concentration sensor group includes turbidity sensors, conductivity sensors, and ion-selective electrodes set in different zones of the tank.
3. The intelligent wastewater treatment dosing device according to claim 1, characterized in that: The intelligent analysis unit includes an abnormal operating condition identification submodule based on a neural network and a dosing prediction submodule based on a fuzzy control algorithm. The two submodules achieve collaborative decision-making through a data fusion processor.
4. The intelligent wastewater treatment dosing device according to claim 1, characterized in that: Each dosing channel of the dynamic dosing control module is equipped with a high-precision metering pump and an electromagnetic regulating valve. The metering pump has a flow resolution of 0.1 mL / min, and the electromagnetic regulating valve has a response time of less than 50 ms.
5. The intelligent wastewater treatment dosing device according to claim 1, characterized in that: The feedback adjustment module establishes a closed-loop control system that includes a feedforward-feedback composite control mechanism. By comparing the deviation between the actual treatment effect and the preset index in real time, it dynamically corrects the weight parameters of the dosing decision algorithm model.
6. The intelligent wastewater treatment dosing device according to claim 1, characterized in that: It also includes a remote monitoring terminal, which is connected to the intelligent analysis unit via a wireless communication module and integrates an anomaly alarm unit, a data visualization interface, and a manual intervention interface.
7. The intelligent wastewater treatment dosing device according to claim 1, characterized in that: The drug storage container is designed to prevent crystallization and is equipped with an ultrasonic oscillator and a balance monitoring sensor inside, and is connected to an automatic drug replenishment pipeline system on the outside.