WWTP Process Control
Imported-Instrument Replacement at Hangzhou Qige WWTP (1.2 Million m³/d)
1 / 2Project Background
Hangzhou Qige wastewater treatment plant — 1.2 million m³/day on an A²/O process with Class 1B effluent — was built entirely on imported instruments, whose procurement and long-term maintenance costs had become a heavy burden.
Customer Challenge
The plant's biological process leans hard on accurate MLSS, dissolved-oxygen, pH and ORP data. Replacement instruments had to match imported performance in a demanding megacity plant — and prove themselves over years, not months.
The TENGINE Solution
TENGINE deployed 39 online monitoring instruments — MLSS suspended-solids meters, LDO luminescent dissolved-oxygen analyzers, pH and ORP meters — replacing the original imported units at the A²/O process's key stages and feeding continuous data to aeration and sludge-return control.
Implementation
The 39 instruments were swapped in at the key process points, integrating with the plant's existing control system without disrupting operation.
Project Results
The replacement instruments have run stably for nearly five years — validating domestic instrumentation at the scale of a million-tonne municipal plant. Procurement and maintenance costs are down, the biological system runs stably, and the project has become a reference for domestic substitution in large wastewater plants.
Related Case Studies
A mega-project of this scale places extreme demands on water quality data — accuracy and stability must hold over decades of operation. The wastewater treatment works required continuous online monitoring of oil content in water: a demanding measurement that has to run unattended in a harsh coastal desert environment, resist fouling, and integrate cleanly into plant process control.
Membrane performance calibration demands precise, time-aligned and traceable water-quality data to verify retention, anti-fouling and cleaning-recovery behavior. The pain points were acute: micro-leakage is hard to detect, and instrument drift under variable operating conditions contaminates the baseline data that the whole evaluation depends on.
Sludge concentration and blanket-level measurement were unreliable, so discharge relied on operator experience. Timing and volume were hard to control precisely — under-discharge, over-discharge and sludge loss all occurred, destabilizing effluent quality and pushing up running costs.
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