The automated control system of ultrafiltration pure water equipment integrates sensor networks, intelligent algorithms, and actuators to construct a complete membrane fouling early warning and intelligent backwashing mechanism. Its core logic revolves around "real-time monitoring - precise diagnosis - dynamic response." The system first continuously collects key parameters such as transmembrane pressure difference, permeate flow rate, influent turbidity, and particle count using various types of sensors deployed at the inlet and outlet of the ultrafiltration membrane module, the membrane fiber surface, and key nodes. These sensors act like the "nerve endings" of the equipment, capturing subtle changes in the early stages of membrane fouling. For example, a slow increase in transmembrane pressure difference may indicate membrane pore blockage, while fluctuations in permeate flow rate may reflect the accumulation of deposits on the membrane fiber surface.
Based on data acquisition, the automated control system relies on intelligent algorithms to achieve precise diagnosis of membrane fouling. Traditional systems often rely on fixed thresholds to trigger alarms, while modern intelligent systems use dynamic models and machine learning techniques to establish predictive models of membrane fouling development by analyzing the correlation between historical operating data and real-time parameters. For example, the system records the evolution of membrane fouling under different water quality conditions and dynamically adjusts the fouling early warning threshold based on the current influent water quality characteristics. When monitoring data deviates from the normal range, the system further analyzes multiple parameters to determine the type of fouling: colloidal fouling, organic fouling, or inorganic scaling, thus providing a basis for subsequent backwashing strategies.
The accuracy of membrane fouling early warning directly determines the timeliness of intelligent backwashing. Once the system determines that membrane fouling has reached a level requiring intervention, the automated control system immediately initiates the intelligent backwashing program. Unlike traditional timed backwashing or backwashing triggered by a single parameter, intelligent backwashing dynamically adjusts backwashing parameters based on the type and degree of fouling, including backwashing flow rate, pressure, time, and chemical dosage. For example, for colloidal fouling, the system may use high-frequency pulse backwashing combined with air scrubbing to remove deposits from the membrane fiber surface through the "water hammer effect"; while for organic fouling, a low concentration of oxidant may be added to assist in the decomposition of organic matter on the membrane surface. This targeted backwashing strategy significantly improves cleaning efficiency while avoiding damage to the membrane fibers from excessive backwashing.
The execution of intelligent backwashing also relies on the precise control of the automated control system. The system utilizes variable frequency drive (VFD) technology to adjust the backwash pump speed in real time, ensuring that backwash flow and pressure remain stable within the set range and preventing membrane fiber breakage due to pressure fluctuations. Simultaneously, the system monitors the quality of the backwash effluent; when the turbidity or particle count drops to a set value, it automatically terminates backwashing to avoid water waste. Some advanced systems also incorporate a backwash effect evaluation mechanism, quantifying the backwash effect by comparing the performance parameters of the membrane modules before and after backwashing, and providing data support for optimizing subsequent backwash strategies.
The automated control system of ultrafiltration pure water equipment also possesses self-learning and adaptive capabilities. Through the accumulation of long-term operational data, the system can identify membrane fouling characteristics under different water quality conditions and operating conditions, and automatically optimize warning thresholds and backwash strategies. For example, in areas with significant seasonal variations in influent water quality, the system can predict high-incidence periods of fouling based on historical data, adjusting operating parameters or increasing backwash frequency in advance for proactive prevention. This adaptive capability significantly improves the operational stability of the equipment and reduces the need for manual intervention.
Furthermore, the automated control system utilizes Internet of Things (IoT) technology to achieve remote monitoring and fault diagnosis. Maintenance personnel can view equipment operating status, membrane fouling warnings, and backwashing records in real time through a cloud platform, and quickly locate the fault point when the system issues an abnormal alarm. For example, if a certain group of membrane modules frequently triggers fouling warnings, the system will prompt the maintenance personnel to check the feed water quality or backwashing effect of that module, assisting maintenance personnel in quickly resolving the problem and reducing downtime.
The automated control system of ultrafiltration pure water equipment constructs an efficient and reliable membrane fouling warning and intelligent backwashing system through multi-parameter real-time monitoring, intelligent algorithm diagnosis, dynamic backwashing strategies, precise execution control, self-learning optimization, and remote maintenance support. This system not only extends the service life of ultrafiltration membranes and reduces maintenance costs, but also ensures the long-term stable operation of ultrafiltration pure water equipment, providing high-quality water resource guarantees for industrial production, municipal water supply, and other fields.
