Pre processor for ventilation measurement analysis.

It is well known that the introduction of tracer gas techniques to ventilation studies has provided much useful information that used to be unattainable from conventional measuring techniques. Data acquisition systems (DASs) containing analog-to-digital (ND) converters are usually used to perform the key role which is reading and saving signals to storage in digital format. In the measuring process, there are a number of components in the measuring equipment which may produce system-based noise fluctuations to the final result. These unwanted fluctuations may cause discrepancy in computations, especially when non-linear algorithms are involved. In this study, a pre-processor is developed and used to separate the unwanted fluctuations (noise or interference) in raw measurements and to reduce the uncertainty in the measurement. Moving average, Notch filter, FIR (Finite Impulse Response) filters, and IIR (Infinite Impulse Response) filters are designed and applied to collect the desired information from the raw measurements. Tracer gas concentrations are measured during leakage and ventilation tests in a model test room. The signal analysis functions embedded in Matlab are used to carry out the digital signal processing (DSP) work.