Soft Sensor / Soft Sensor Design Patterns

Soft Sensor Design Patterns

Sourced case studies from published industrial deployments of soft sensors, virtual sensors, and state estimation systems.

3 patterns published

01

NOx Emission Soft Sensor for Thermal Power Plants

A just-in-time-learning random forest soft sensor predicts NOx concentration from thermal power plant process data, reaching R² = 0.93 on the test set and outperforming the six comparison models of the study.

EnergyPower Generation
Read pattern → 02

Soft Sensor for Effluent Quality in Onsite Wastewater Treatment

Machine-learning soft sensors predict COD and TSS of an onsite wastewater treatment system from in-line water-quality sensors: support vector regression reached R² = 0.96 for COD and cubist regression R² = 0.99 for TSS.

Water & WastewaterMunicipal Infrastructure
Read pattern → 03

Soft Sensor for Melt Flow Index in Polymerization Reactors

An inferential sensor estimates melt flow index (MFI) continuously from process measurements, so quality control does not have to wait for laboratory results that arrive hours later.

ChemicalsPolymer Production
Read pattern →

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