Integration of Digital Filters and Measurements
Jan Peter · InTech eBooks · 2011
Digital filters (Hamming, 1998; Chen, 2001) are versatile, practical and effective. They can be used in most computerized applications of modern technology and science. Nearly every person in technologically developed regions daily encounter digital filters in cars, dvdrecorders, computers, telecommunication systems etc. Usually, digital filters are designed and optimized by signal processing experts for standardized tasks in specific systems. Extensive work may result in advanced and complex filters. This is motivated by massive duplication. The marginal production cost for a filter is practically zero and the development cost per unit is negligible. The advantages of using digital instead of analogue filters are often profound. Not only are the costs negligible, their flexibility makes it possible to achieve superior results. Even unstable operations can be realized by means of reversed filtering. The limitations of digital filters are mainly mathematical, rather than physical as for analogue filters. Dynamic measurements condense observations into quantitative representations (Hessling, 2010a). Dynamic methods for improving, interpreting and assessing the quality of measurements are relatively scarce. These methods can be formulated in terms of ideal prototype systems acting on physical signals to produce the desired information. A dynamic calibration procedure is usually required to find the model from which such prototypes are determined. Ideal prototypes are approximated and optimized into realizable prototypes which can be cast into digital filters by means of sampling. These filters differ from most common filters of today. They are dedicated filters with a high level of adaptation and flexibility, designed to improve or simplify the evaluation of a wide range of measurements for many different purposes. The common denominator of all filters is that they are intended to provide a supporting link of standardized dynamic analysis between the ‘raw’ measurements and an inexperienced destined user. The digital filters and the measurement devices are preferably seamlessly integrated in the final application, which most often already has a computer program for administrating the measurement. The motivation for making any measurement is to extract information. The desired information is rarely identical to measured signals. Measured signals need to be processed or analyzed. Signals may be corrected. To determine how wrong the result might be, the uncertainty needs to be estimated. The measurement system may be one part of a complex dynamic system, for instance, an accelerometer attached to a vibrating vehicle. Sometimes transformations between various points in space, or electrical quantities etc. are required. We might be interested in the consequences of measured signals. The impact of interest is 6