1. Project Background

A textile dyeing and finishing plant in Suzhou, Jiangsu Province treats wastewater containing high concentrations of organic compounds. To comply with increasingly strict environmental regulations, the plant needed continuous online monitoring of chemical oxygen demand (COD) to ensure treated water met discharge standards.

KWS-100 Online COD Sensor in Industrial Wastewater Treatment

2. Wastewater Characteristics and Monitoring Requirements

The plant’s wastewater has significant COD variability due to the use of dyes, chemical additives, and solvents during production. Monitoring requirements included:

  • High variability in COD concentration
  • Real-time monitoring to allow timely adjustment of coagulant and oxidizing agents
  • Compliance with discharge regulations: COD <100 mg/L for treated water

The KWS-100 sensor was selected to provide real-time feedback on COD fluctuations, optimize treatment efficiency, and reduce chemical overuse.

3. System Configuration and Installation

The KWS-100 sensor was installed on the main inlet pipe of the wastewater treatment system:

  • KWS-100 Online COD Sensor
    • Range: 0–1000 mg/L
    • Output: RS485 (Modbus RTU)
    • Installation: Immersion type, ensuring stable contact with flow and easy maintenance
    • Housing Material: 316L stainless steel, resistant to industrial corrosion
    • Automatic Cleaning: Reduces fouling, maintains measurement stability
  • Integration:
    RS485 output connected to the plant PLC system for continuous monitoring, trending, and process feedback.
KWS-110 Online COD Sensor 800x800

4. Operational Performance

Since deployment, the KWS-100 sensor has provided reliable online data:

  • Normal operation COD: 60–80 mg/L
  • Peak COD during high production: 120–150 mg/L
  • Rapid response to COD spikes allowed timely adjustment of chemical dosing
  • After 8 months of operation, statistical analysis shows over 95% of COD measurements remain below 100 mg/L, confirming stable wastewater quality and reliable sensor performance

5. Project Summary