Layer / Tomczyk Measurements, Modelling and Simulation of Dynamic Systems

1. Auflage 2009
ISBN: 978-3-642-04588-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 156 Seiten

The development and use of models of various objects is becoming a more common practice in recent days. This is due to the ease with which models can be developed and examined through the use of computers and appropriate software. Of those two, the former - high-speed computers - are easily accessible nowadays, and the latter - existing programs - are being updated almost continuously, and at the same time new powerful software is being developed. Usually a model represents correlations between some processes and their interactions, with better or worse quality of representation. It details and characterizes a part of the real world taking into account a structure of phenomena, as well as quantitative and qualitative relations. There are a great variety of models. Modelling is carried out in many diverse fields. All types of natural phenomena in the area of biology, ecology and medicine are possible subjects for modelling. Models stand for and represent technical objects in physics, chemistry, engineering, social events and behaviours in sociology, financial matters, investments and stock markets in economy, strategy and tactics, defence, security and safety in military fields. There is one common point for all models. We expect them to fulfil the validity of prediction. It means that through the analysis of models it is possible to predict phenomena, which may occur in a fragment of the real world represented by a given model. We also expect to be able to predict future reactions to signals from the outside world.

Autoren/Hrsg.

Tomczyk, Krzysztof

Layer, Edward

Inhaltsverzeichnis

1;Preface;5
2;Contents;9
3;Introduction to Measuring Systems;11
3.1;Sensor;13
3.2;Transducer;13
3.3;Matching Circuit;13
3.4;Anti-aliasing Filter;13
3.5;Multiplexers/Demultiplexers;16
3.6;Sample-and-Hold Circuit;18
3.7;Analogue-to-Digital Conversion;20
3.7.1;A/D Converter with Parallel Comparison;20
3.7.2;A/D Converter with Successive Approximation;22
3.7.3;Integrating A/D Converters;27
3.7.4;Sigma Delta A/D Converter;32
3.8;Input Register;34
3.9;Digital-to-Analogue Conversion;35
3.10;Reconstruction Filter;36
3.11;DSP;37
3.12;Control System;38
3.13;References;38
4;Sensors;39
4.1;Strain Gauge Sensors;39
4.1.1;Temperature Compensation;41
4.1.2;Lead Wires Effect;43
4.1.3;Force Measurement;44
4.1.4;Torque Measurement;45
4.1.5;Pressure Measurement;45
4.2;Capacitive Sensors;48
4.3;Inductive Sensors;50
4.4;Temperature Sensors;55
4.5;Vibration Sensors;61
4.5.1;Accelerometer;61
4.5.2;Vibrometer;64
4.6;Piezoelectric Sensors;66
4.7;Binary-Coded Sensors;69
4.8;References;72
5;Methods of Noise Reduction;73
5.1;Weighted Mean Method;73
5.2;Windows;75
5.3;Effect of Averaging Process on Signal Distortion;77
5.4;Efficiency Analysis of Noise Reduction by Means of Filtering;82
5.5;Kalman Filter;88
5.6;References;92
6;Model Development;93
6.1;Lagrange Polynomials;94
6.2;Tchebychev Polynomials;96
6.3;Legendre Polynomials;100
6.4;Hermite Polynomials;103
6.5;Cubic Splines;105
6.6;The Least-Squares Approximation;111
6.7;Relations between Coefficients of the Models;112
6.8;Standard Nets;115
6.9;Levenberg-Marquardt Algorithm;121
6.9.1;Implementing Levenberg-Marquardt Algorithm Using LabVIEW;123
6.10;Black-Box Identification;125
6.11;Implementing Black-Box Identification Using MATLAB;127
6.12;Monte Carlo Method;133
6.13;References;134
7;Mapping Error;137
7.1;General Assumption;137
7.2;Signals Maximizing the Integral Square Error;138
7.2.1;Existence and Availability of Signals with Two Constraints;138
7.2.2;Signals with Constraint on Magnitude;140
7.2.3;Algorithm for Determining Signals Maximizing the Integral Square Error;141
7.2.4;Signals with Two Constraints;144
7.2.5;Estimation of the Maximum Value of Integral Square Error;149
7.3;Signals Maximizing the Absolute Value of Error;150
7.3.1;Signals with Constraint on Magnitude;150
7.3.2;Shape of Signals with Two Constraints;150
7.4;Constraints of Signals;158
7.5;References;159
8;Index;161