Doprinos projektovanju i primeni pseudoslučajnih i entropijskih kodova u digitalnim mernim sistemima

Abstract

This dissertation considers the design and implementation of pseudorandom and entropy codes in digital measuring systems. Using those codes, performances of measurement systems can be significantly improved. Pseudorandom binary codes (based on pseudorandom binary sequences) are widely used in many measurement systems; and one of the most important application lies in the realization of pseudorandom position encoders. Application of pseudorandom codes allows the increase of resolution of the position encoder without increasing of complexity and cost; also, it allows implementation of methods for the fault detection and direct setting of the zero position. The dissertation mainly discusses the design of the converters of the pseudorandom code into natural binary code; some of the most important contributions of the dissertation are derivation of a generalized formula for the design of the initial logic of Galois code converter for any resolution, as well as the improvement of the realization of serial code converters by modification of the way how bits are written into flip flops of the shift register, which reduces the conversion time and increases the efficiency of the converter. Another type of codes considered in the dissertation are entropy codes (also known as codes with variable length codewords), which are used in order to achieve compression of measurement signals. Compression of measurement signal is particularly important in modern wireless measurement systems (telemetry and telemedicine systems, wireless sensor networks); in these systems, due to limited resources (limited energy of nodes, limited capacity of the wireless channel and limited memory), it is necessary to reduce the amount of measurement data for wireless transmission by applying a compression algorithm. There are the large number of existing compression algorithms, but they are not developed for measurement signals (but for other types of signals, primarily for multimedia signals) and are not adapted to them; also, due to the high complexity of existing compression algorithms, they cannot be implemented on the sensor nodes with very limited hardware resources and processing capability. Hence, the most of existing compression algorithms cannot be directly applied in wireless measurement systems. Therefore, it is necessary to develop new compression algorithms, which will take into account the specificities of measurement signals and hardware limitations of sensor nodes in measurement systems. Several algorithms for compression of measurement signals, based on quantization and entropy coding, are proposed in the dissertation. The proposed algorithms will be firstly described in general form so that it can be applied to a broad class of measurement signals; after that, they will be specifically adjusted and applied for compression of vibration and ECG signals. These signals were chosen due to importance they have and due to the growing number of wireless measurement systems dedicated to these types of signals, where signal compression is a necessity. It is shown that the proposed compression algorithms, although with small complexity, can achieve very good performances, similar or even better than other models in the literature. All results in the dissertation are validated by simulations; also, an experimental measurement system for measurement, compression and wireless transmission of vibration signals are realized, implementing compression algorithms previously described in the dissertation.