Where measurement values aren't sifted 08/12/2015 What performance level can you expect from the sensors applied? This question cannot be answered by simply taking a look at the catalog or data sheet. The data from different suppliers cannot be compared at first glance. It's all about the small print, which will give you an overview about how these values were determined. Were filters used? Have the measurement values been smoothed? At first, this is not clearly visible, but may only be partially noted with footnotes. We determine the accuracy of our sensors using raw values and indicating these in our catalogs and data sheets. We therefore build trust and help customers to solve their application-related challenges. You therefore have a precise overview of which sensor achieves what performance level in a specific environment. However, should you require filtering methods for optimizing measurement results for your specific application, we offer you many different options. As marginal conditions of applications influence the sensor signal, interpretation and further processing of the signal are often complex. If signal noise, invalid measurement values or signal peaks are undesirable due to specific requirements of the production process, special filter techniques can eliminate these in a simple way. Micro-Epsilon likes to guide you on which sensor to use and the application-related choice of filters. The average output of a certain number of values can only be done via an arithmetic average. Using the moving average, the measurement values can be smoothed, for example, in order to filter out surface roughness. Recursive averaging enables very good smoothing of the measured values. The median suppresses individual interference pulses and the edge filter smoothes signals at transitions such as edges or surface changes, thus avoiding signal overshooting. For more details and a corresponding description of filters and averaging applicable to Micro-Epsilon sensors, please refer to the TechNote.