A novel pattern mismatch based interference elimination technique in E-nose

Metal oxide semiconductor (MOS) sensor array with cross-sensitivity to target gases is often used in electronic nose (e-nose) for monitoring indoor air quality. However, MOS sensors have their own defects of high susceptibility to some interferences which would seriously impact on the detection of target gases. Therefore it is urgent to solve the problem of interferences elimination as e-nose composed of MOS sensors cannot be used when there are interferences. A closely related method tends to discriminate the interference gases and target gases, and it depends on the type of interference gases. However, there are numerous interferences in real-world application scenario, which is impossible to be sampled in laboratory experiments. Considering that target gases detected by an e-nose can be fixed as invariant information, a novel and effective Pattern Mismatch based Interference Elimination (PMIE) method is proposed in this paper. It contains two parts: interference discrimination (i.e. pattern mismatch) and correction (i.e. interference elimination). Specifically, the principle of interference discrimination is whether a new pattern violates the rules established on the invariant target gases information (i.e. the case of interference gas appearing) or not (i.e. the case of only target gas appearing). If the current pattern of the sensor array is of interference, orthogonal signal correction algorithm (OSC) is used for interference correction. Experimental results prove that the proposed PMIE method is significantly effective for interference elimination in e-nose.