A soft sensor is widely used as a alternative for process monitoring

but robust problems prevailing in soft sensor application hinder its further usage. A novel soft sensor such as self-validating soft sensor is proposed

which not only deals with input data online calibration and fault reconstruction problems

but also further ensures the reliability of input data by performing Principal Component Analysis (PCA) analysis. In addition

uncertainties are characterized by output variance and inductive confidence predictor (ICP). The output with uncertainties

model statuses uncertainties

faulty messages and validated output are implemented for ensuring proper fault reconstruction and model calibration. The effectiveness was proved in a wastewater treatment process.