Intelligent Process Analysis and Intelligent Control

I. Product Introduction

The process intelligent analysis and intelligent control system is a core application module of the visualized smart platform for wastewater treatment plants. By integrating wastewater treatment process parameters, online water quality monitoring data, equipment operating status, and historical production data, the system continuously analyzes the wastewater treatment process, helping operators understand process status, identify abnormal changes, and optimize equipment operation and process control strategies.

The system can combine wastewater treatment process models, control rules, data analysis algorithms, andanalysis algorithms according to project requirements.technology to analyze aeration systems, water pump systems, chemical dosing systems, and other key treatment links, helping management personnel discover operational problems, improve control strategies, and, while meeting process conditions and safety requirements, achieve automatic execution of some control strategies.

The platform supports data interaction with, variable-frequency drives, dosing equipment, and other actuators, and feed back equipment operating status and process data.MBR , level gauges, flow meters, dissolved oxygen meters,, online monitoring equipment, and on-site actuators.PLC is responsible for basic control, interlock protection, and key control logic of on-site equipment; the intelligent analysis module is responsible for process analysis, anomaly identification, optimization suggestions, and calculation of validated control strategies. The two work collaboratively, enabling wastewater treatment to gradually develop from traditional fixed-logic control toward data-driven refined operation optimization.

The specific analysis models, control scope, and degree of automation are determined according to the wastewater treatment process, on-site instrument configuration, equipment conditions, and project requirements.

II. Main Functions

1. Process Operation Status Analysis

Conduct comprehensive analysis of real-time and historical data generated during the wastewater treatment process to help operators understand the operating status of each treatment unit.

Main analysis contents include:

Tracking of energy-saving optimization effects Analysis of influent flow and load changes

Tracking of energy-saving optimization effects Analysis of operating parameters of biological treatment units

Tracking of energy-saving optimization effects Trend analysis of key process parameters such as dissolved oxygen andmeters, online water quality monitoring equipment, electric energy metering equipment, and other on-site data sources.l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects Through comprehensive analysis of multiple process data, assist in identifying operational fluctuations, parameter anomalies, and potential process problems, providing a basis for operational adjustments.

2. Anomaly Identification and Intelligent Alarming

Based on process setpoints, historical data, change trends, and analysis rules, the system identifies abnormal conditions that may affect the stability of wastewater treatment.

Main functions include:

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Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects When sufficient data and validated analysis models are available, complex parameter correlations and potential anomalies can be further identified. Alarm results are used to assist judgment and cannot directly replace online water quality testing, laboratory testing, or professional process judgment.

3. Intelligent Optimization of Aeration System

The aeration system is usually an important energy-consuming link in the wastewater biological treatment process. The platform can combine dissolved oxygen, influent load, blower operating status, aeration equipment parameters, and related process data to assist in analyzing the relationship between aeration demand and energy consumption.

Main functions include:

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Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects When corresponding instruments, variable-frequency equipment, and control interfaces are available, the blower operating frequency or related setpoints can be automatically adjusted according to validated control strategies.

Aeration optimization needs to consider biological process characteristics, sensor reliability, and effluent water quality requirements, and cannot determine all control strategies based solely on a single dissolved oxygen value.

4. Optimization of Water Pump and Conveying System

The system combines liquid level, flow, equipment status, operating time, and energy consumption data to analyze influent lifting, return flow, sludge conveying, and other pumping links.

Main functions include:

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Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects While meeting on-site equipment capacity and process requirements, validated operating strategies can be applied to the

PLC control system to form a closed-loop process from data collection and analysis calculation to control execution and effect feedback.5. Intelligent Optimization of Chemical Dosing System

For coagulation, flocculation,

pH meters, online water quality monitoring equipment, electric energy metering equipment, and other on-site data sources.Main functions include:

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Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects When the project has reliable online detection, suitable control models, and available metering and dosing equipment, automatic dosing control can be further implemented.

Actual chemical dosing strategies should be based on water quality characteristics, process conditions, and treatment effect verification, avoiding the direct use of unvalidated

AI analysis algorithms according to project requirements.6. Process Parameter Optimization and Control Strategy Management

The system can assist in forming control strategies under different operating conditions based on wastewater treatment process objectives, equipment capacity, operating constraints, and historical operating performance.

Main functions include:

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Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects For projects requiring automatic adjustment, the system can send confirmed control parameters or optimization instructions to the on-site control system, where the

PLC control system to form a closed-loop process from data collection and analysis calculation to control execution and effect feedback.7. Collaborative Analysis of Energy Consumption and Treatment Effect

The system combines and analyzes process operation data, treated water volume, equipment operating status, and energy consumption data to assist in evaluating the impact of operating strategies on treatment effect and energy consumption.

Main functions include:

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Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects l

Tracking of energy-saving optimization effects Through comprehensive analysis of treatment effect and energy consumption indicators, help management personnel find more reasonable operating modes while meeting treatment requirements.

8. Automatic Control and Closed-Loop Optimization

When the project has complete on-site detection, control equipment, communication interfaces, and safety protection conditions, intelligent analysis results can be combined with the

PLC control system to form a closed-loop process from data collection and analysis calculation to control execution and effect feedback.Typical process:

On-site instruments collect data

→ PLC/SCADA uploads data → feeds back operation results.→ feeds back operation results.→ feeds back operation results.→ PLC executes control → feeds back operation results.It can be applied to aeration regulation, water pump operation optimization, dosing control, and other process-validated scenarios.

The scope of automatic control should be determined item by item according to the project. Protection of key equipment, emergency stop, necessary interlocks, and basic control logic should remain in the on-site control system, with appropriate manual takeover, strategy exit, and abnormal degradation mechanisms.

III. Typical Application Scenarios

1

, MBR Conduct operation analysis and optimization for influent load, biological treatment, aeration, sludge treatment, and other links. 2

, MBR Based on specific water quality characteristics and treatment processes, analyze changes in operating parameters and assist in identifying process anomalies. 3

, MBR When data conditions permit, assist in optimizing the operation of blowers, water pumps, and other equipment to reduce unnecessary energy consumption. 4

, MBR Centrally compare operating parameters, energy consumption, and equipment status of different sites, providing a basis for unified management and optimization. IV. System Composition and Technical Architecture

1. Data Collection Layer

Includes

PLC, variable-frequency drives, dosing equipment, and other actuators, and feed back equipment operating status and process data.MBR , level gauges, flow meters, dissolved oxygen meters,pH meters, online water quality monitoring equipment, electric energy metering equipment, and other on-site data sources.2. Data Management Layer

Responsible for organizing, storing, and correlating real-time data, historical data, equipment status, and process operation records, providing a data foundation for analysis models.

3. Process Analysis Layer

Configure process rules, statistical analysis, anomaly identification, control models, or

AI analysis algorithms according to project requirements.4. Optimization Decision Layer

Generate operation recommendations, setpoint recommendations, or validated control strategies according to process objectives and operating constraints, and record strategies and their execution.

5. On-Site Execution Layer

Implement permitted control actions through

SCADA , variable-frequency drives, dosing equipment, and other actuators, and feed back equipment operating status and process data.6. Monitoring and Management Layer

Display analysis results and operation effects through

SCADA screens, trend curves, alarm interfaces, and 3D digital twin scenarios.V. Customized Services

Customized according to wastewater treatment process

Based on

A²/O, oxidation ditch,SBR, MBR or other actual processes, determine the key parameters that can be analyzed and the applicable optimization scenarios.Customized according to on-site equipment

Combined with the configuration of blowers, water pumps, variable-frequency drives, dosing systems, and online instruments, determine the feasible control scope.

Customized according to data foundation

Evaluate the applicability of analysis models based on historical data completeness, sensor accuracy, data sampling frequency, and communication conditions.

Customized according to degree of automation

Different methods such as operation analysis and recommendations, execution after manual confirmation, or implementation of automatic closed-loop control when conditions are met can be adopted.

Customized according to project objectives

Specific plans can be formulated around objectives such as process stability, equipment operating efficiency, energy consumption management, anomaly alarming, or chemical consumption.

VI. System Application Value

Improve process visibility:

Comprehensively analyze multiple process data to help operators understand the wastewater treatment process more fully. Assist in anomaly identification:

Promptly discover parameter changes and equipment operation anomalies, and support troubleshooting. Optimize equipment operation:

Provide operating strategy references for aeration, water pumps, dosing, and other links. Support energy saving and consumption reduction:

Combine treated water volume, equipment status, and energy consumption data to identify optimization space. Improve management efficiency:

Record analysis results, control strategies, and operation feedback in a unified manner for easy tracking and evaluation. Support continuous optimization:

Use historical data and actual operation effects to gradually improve process analysis and control strategies. VII. Obtain a Customized Solution

If you need to build a wastewater plant process intelligent analysis and intelligent control system, please provide the wastewater treatment process flow,

PLC/SCADA system information, online instrument list, main equipment configuration, historical operation data, and expected optimization objectives.We can evaluate the feasible analysis scenarios, control scope, and system integration method based on the on-site data foundation and automation conditions, and formulate corresponding process intelligence solutions.