An interferogram obtained from a transparent plate contains information on the profiles of both surfaces and on the thickness variation. The present work is devoted to the processing of interferograms of this type. The processing technique is based on a 36-step algorithm developed by the authors for characterization of transparent plates having approximately equal reflections from both sides. The algorithm utilizes weighted multi-step phase shifting that enables one not only separately to extract the front and rear surface profiles together with the thickness variation of the tested plate but also to suppress the coupling errors between the higher harmonics and phase-shift deviation. The proposed measuring method was studied on a wavelength tunable Fizeau interferometer. The tested sample had an optical thickness and surface profile deviations equal to 0.51 µm, 1.38 µm and 0.89 µm, respectively. According to the results obtained using 10 repeated measurements, the root mean square (RMS) errors for determining both surface profiles did not exceed 1.5 nm. Experimental results show that the setup and presented 36-step algorithm are suitable for the measurement of a transparent plate of arbitrary thickness.
1 January 2008 in International Journal on Smart Sensing and Intelligent Systems
A significant proportion of the atmospheric pollution that exists particularly in urban areas arises from road vehicles and primarily cars. The European Commission (EC) have introduced a series of regulations, the so called EURO Emission directives from Euro I in 1991 to the present day Euro IV. This legislation and similar ones in other global regions have helped to greatly reduce emission levels from road transport. However, a massive increase in the number of cars on the road have meant that pollution due to a number of gases and particulate species remains to be a problem. This paper describes an approach based on optical fibre sensors which has shown to be an effective means of measuring the gases and particulates in question by using sensing technologies which are both robust and potentially cost effective such that they may be included as part of an on board monitoring system for the car of the future.