Methods for the analysis of two dimensional measurement data of paper web

This work is devoted to the problem of reconstructing the basis weight structure at paper web with black{box techniques. The data that is analyzed comes from a real paper machine and is collected by an o®-line scanner. The principal mathematical tool used in this work is Autoregressive Moving Average (ARMA) modelling. When coupled with the Discrete Fourier Transform (DFT), it gives a very flexible and interesting tool for analyzing properties of the paper web. Both ARMA and DFT are independently used to represent the given signal in a simplified version of our algorithm, but the final goal is to combine the two together. Ljung-Box Q-statistic lack-of-fit test combined with the Root Mean Squared Error coefficient gives a tool to separate significant signals from noise.

Quantile Estimation in Non-Stationary Streaming Data

We provide an incremental quantile estimator for Non-stationary Streaming Data. We propose a method for simultaneous estimation of multiple quantiles corresponding to the given probability levels from streaming data. Due to the limitations of the memory, it is not feasible to compute the quantiles by storing the data. So estimating the quantiles as the data pass by is the only possibility. This can be effective in network measurement. To provide the minimum of the mean-squared error of the estimation, we use parabolic approximation and for comparison we simulate the results for different number of runs and using both linear and parabolic approximations.

Development of a PC Tool for Estimating Pressure Drops in Forced-convection Boiler Tubes

Kaksifaasivirtauksen kuvaamiseen käytettävät mallit, ja menetelmät kaksifaasivirtauksen painehäviön määrittämiseksi kehittyvät yhä monimutkaisimmiksi. Höyrystinputkissa tapahtuvien painehäviöiden arvioinnin vaatiman laskennan suorittamiseksi tietokoneohjelman kehittäminen on välttämätöntä. Tässä työssä on kehitetty itsenäinen PC-ohjelma painehäviöiden arvioimiseksi pakotetulle konvektiovirtaukselle pystysuorissa höyrykattilan höyrystinputkissa. Veden ja vesihöyryn aineominaisuuksien laskentaan käytetään IAPWS-IF97 –yhtälökokoelmaa sekä muita tarvittavia IAPWS:n suosittelemia yhtälöitä. Höyrystinputkessa kulloinkin vallitsevan virtausmuodon määrittämiseen käytetään sovelluskelpoisia virtausmuotojen välisiä rajoja kuvaavia yhtälöitä. Ohjelmassa käytetään painehäviön määritykseen kirjallisuudessa julkaistuja yhtälöitä, virtausmuodosta riippuen, alijäähtyneelle virtaukselle, kupla-, tulppa- ja rengasvirtaukselle sekä tulistetun höyryn virtaukselle. Ohjelman laskemia painehäviöarvioita verrattiin kirjallisuudesta valittuihin mittaustuloksiin. Laskettujen painehäviöiden virhe vaihteli välillä –19.5 ja +23.9 %. Virheiden itseisarvojen keskiarvo oli 12.8 %.

Kohinan poisto spektrikuvista pehmeillä morfologisilla suodattimilla

Tämän diplomityön tavoitteena oli tutkia kohinan poistoa spektrikuvista käyttäen pehmeitä morfologisia suodattimia. Työssä painotettiin impulssimaisen kohinan suodattamista. Suodattimien toimintaa arvioitiin numeerisesti keskimääräisen itseisarvovirheen, neliövirheen sekä signaali-kohinasuhteen avulla ja visuaalisesti tarkastelemalla suodatettuja kuvia sekä niiden yksittäisiä spektritasoja. Käytettyjä suodatusmenetelmiä olivat suodatus kuvapisteittäin spektrin suunnassa, suodatus koko spektrissä sekä kuutiomenetelmä ja komponenteittainen suodatus. Suodatettavat kuvat sisälsivät joko suola ja pippuri- tai bittivirhekohinaa. Parhaimmat suodatustulokset sekä numeeristen virhekriteerien että visuaalisen tarkastelun perusteella saatiin komponenteittaisella sekä kuvapisteittäisellä menetelmällä. Työssä käytetyt menetelmät on esitetty algoritmimuodossa. Suodatinalgoritmien toteutukset ja suodatuskokeet tehtiin Matlab-ohjelmistolla.

Use of neural networks in robot positioning of large flexible redundant manipulators

Deflection compensation of flexible boom structures in robot positioning is usually done using tables containing the magnitude of the deflection with inverse kinematics solutions of a rigid structure. The number of table values increases greatly if the working area of the boom is large and the required positioning accuracy is high. The inverse kinematics problems are very nonlinear, and if the structure is redundant, in some cases it cannot be solved in a closed form. If the structural flexibility of the manipulator arms is taken into account, the problem is almost impossible to solve using analytical methods. Neural networks offer a possibility to approximate any linear or nonlinear function. This study presents four different methods of using neural networks in the static deflection compensation and inverse kinematics solution of a flexible hydraulically driven manipulator. The training information required for training neural networks is obtained by employing a simulation model that includes elasticity characteristics. The functionality of the presented methods is tested based on the simulated and measured results of positioning accuracy. The simulated positioning accuracy is tested in 25 separate coordinate points. For each point, the positioning is tested with five different mass loads. The mean positioning error of a manipulator decreased from 31.9 mm to 4.1 mm in the test points. This accuracy enables the use of flexible manipulators in the positioning of larger objects. The measured positioning accuracy is tested in 9 separate points using three different mass loads. The mean positioning error decreased from 10.6 mm to 4.7 mm and the maximum error from 27.5 mm to 11.0 mm.

Conventional and nonconventional Kramers-Kronig analysis in optical spectroscopy

This Master’s Thesis is dedicated to the investigation and testing conventional and nonconventional Kramers-Kronig relations on simulated and experimentally measured spectra. It is done for both linear and nonlinear optical spectral data. Big part of attention is paid to the new method of obtaining complex refractive index from a transmittance spectrum without direct information of the sample thickness. The latter method is coupled with terahertz tome-domain spectroscopy and Kramers-Kronig analysis applied for testing the validity of complex refractive index. In this research precision of data inversion is evaluated by root-mean square error. Testing of methods is made over different spectral range and implementation of this methods in future is considered.

Simulation of the Interaction Mean Free Path between Neutrons and TRISO Particles

The interaction mean free path between neutrons and TRISO particles is simulated using scripts written in MATLAB to solve the increasing error present with an increase in the packing factor in the reactor physics code Serpent. Their movement is tracked both in an unbounded and in a bounded space. Their track is calculated, depending on the program, linearly directly using the position vectors of the neutrons and the surface equations of all the fuel particles; by dividing the space in multiple subspaces, each of which contain a fraction of the total number of particles, and choosing the particles from those subspaces through which the neutron passes through; or by choosing the particles that lie within an infinite cylinder formed on the movement axis of the neutron. The estimate from the current analytical model, based on an exponential distribution, for the mean free path, utilized by Serpent, is used as a reference result. The results from the implicit model in Serpent imply a too long mean free path with high packing factors. The received results support this observation by producing, with a packing factor of 17 %, approximately 2.46 % shorter mean free path compared to the reference model. This is supported by the packing factor experienced by the neutron, the simulation of which resulted in a 17.29 % packing factor. It was also observed that the neutrons leaving from the surfaces of the fuel particles, in contrast to those starting inside the moderator, do not follow the exponential distribution. The current model, as it is, is thus not valid in the determination of the free path lengths of the neutrons.