The online pH controller combines electrochemical measurement with intelligent algorithms to achieve real-time and precise control of water acidity and alkalinity. Its working principle and core algorithm can be analyzed as follows:
1、 Principles of Electrochemical Measurement
The controller core adopts a primary battery structure composed of a hydrogen ion glass electrode and a reference electrode. When the electrode is immersed in a solution, the surface of the glass film undergoes ion exchange with hydrogen ions in the solution, forming a potential difference that is logarithmic to the concentration of hydrogen ions. The potential difference is amplified and filtered by the signal conditioning circuit, converted into a 0-5V or 4-20mA standard signal, and finally converted into pH value by the microprocessor. For example, in the wastewater treatment of chemical industrial parks, electrodes need to withstand strong corrosive substances such as fluorine and chlorine, and titanium alloy substrates and polytetrafluoroethylene protective layers need to be used to ensure measurement stability.
2、 Core control algorithm
PID closed-loop control algorithm
Dynamically adjust the dosage of acid and alkali through three links: proportional (P), integral (I), and derivative (D). Taking a sewage treatment plant in the north as an example, when the pH value deviates from the target value by 0.2, the system automatically starts PID regulation: the proportional link quickly responds to the deviation, the integral link eliminates steady-state errors, and the derivative link suppresses overshoot. The factory adopts the fuzzy PID algorithm to shorten the pH adjustment response time from the traditional 15 minutes to 5 minutes, and the overshoot is controlled within ± 0.1.
Nonlinear compensation algorithm
For the nonlinear characteristics of acid-base neutralization processes, segmented linearization or neural network models are used for compensation. For example, in the treatment of chromium containing wastewater, when the pH value approaches the neutral point, the slope of the titration curve suddenly changes. The system uses a nonlinear gain compensation algorithm to improve the accuracy of acid-base flow regulation to 0.1L/min, ensuring that the Cr ⁶⁺ removal rate remains stable at over 98%.
Feedforward feedback composite control
By combining feedforward signals such as inlet flow rate and temperature with feedback regulation of measured pH values, forward-looking control can be achieved. After adopting this mode in a certain park, when the pH value of the incoming water suddenly changes, the system will start the pre adjustment pump for 10 seconds, reducing the pH fluctuation range of the biochemical tank from ± 0.5 to ± 0.2, and reducing the microbial activity inhibition rate by 40%.
3、 Intelligent optimization technology
Modern controllers integrate adaptive algorithms that can automatically identify changes in operating conditions and adjust control parameters. For example, the GREENPRIMAPM8200P controller from the UK uses historical data modeling to predict pH fluctuations 1-2 hours in advance, achieving a 15% reduction in chemicals and a 12% reduction in energy consumption in chemical wastewater treatment. In addition, some devices adopt a dual sensor redundancy design. When the main sensor fails, the backup sensor can seamlessly switch within 0.5 seconds to ensure control continuity.