Wavelets in real-time paper web analysis

Online paper web analysis relies on traversing scanners that criss-cross on top of a rapidly moving paper web. The sensors embedded in the scanners measure many important quality variables of paper, such as basis weight, caliper and porosity. Most of these quantities are varying a lot and the measurements are noisy at many different scales. The zigzagging nature of scanning makes it difficult to separate machine direction (MD) and cross direction (CD) variability from one another. For improving the 2D resolution of the quality variables above, the paper quality control team at the Department of Mathematics and Physics at LUT has implemented efficient Kalman filtering based methods that currently use 2D Fourier series. Fourier series are global and therefore resolve local spatial detail on the paper web rather poorly. The target of the current thesis is to study alternative wavelet based representations as candidates to replace the Fourier basis for a higher resolution spatial reconstruction of these quality variables. The accuracy of wavelet compressed 2D web fields will be compared with corresponding truncated Fourier series based fields.

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.

Kalman Filtering in Online Paper Quality Assessment

Controlling the quality variables (such as basis weight, moisture etc.) is a vital part of making top quality paper or board. In this thesis, an advanced data assimilation tool is applied to the quality control system (QCS) of a paper or board machine. The functionality of the QCS is based on quality observations that are measured with a traversing scanner making a zigzag path. The basic idea is the following: The measured quality variable has to be separated into its machine direction (MD) and cross direction (CD) variations due to the fact that the QCS works separately in MD and CD. Traditionally this is done simply by assuming one scan of the zigzag path to be the CD profile and its mean value to be one point of the MD trend. In this thesis, a more advanced method is introduced. The fundamental idea is to use the signals’ frequency components to represent the variation in both CD and MD. To be able to get to the frequency domain, the Fourier transform is utilized. The frequency domain, that is, the Fourier components are then used as a state vector in a Kalman filter. The Kalman filter is a widely used data assimilation tool to combine noisy observations with a model. The observations here refer to the quality measurements and the model to the Fourier frequency components. By implementing the two dimensional Fourier transform into the Kalman filter, we get an advanced tool for the separation of CD and MD components in total variation or, to be more general, for data assimilation. A piece of a paper roll is analyzed and this tool is applied to model the dataset. As a result, it is clear that the Kalman filter algorithm is able to reconstruct the main features of the dataset from a zigzag path. Although the results are made with a very short sample of paper roll, it seems that this method has great potential to be used later on as a part of the quality control system.

In-line Monitoring of Precipitation Process using Raman Spectroscopy and ATR-FTIR

Polymorfian jatkuva seuranta saostuksessa on hyödyllistä suunnittelun ja kidetuotteen ominaisuuksien sekä kiteytystä seuraavan jatkoprosessoinnin kannalta. Tässä diplomityössä on tutkittu L-glutamiinihapon kahden (- ja ß) polymorfimuodon liukoisuuden riippuvuutta pH:sta ja lämpötilasta.Tulokseksi saatiin, että kummankin polymorfin liukoisuus kasvoi sekä pH:ta ettälämpötilaa kasvatettaessa. ¿¿muodon liukoisuus oli korkeampi kuin ß-muodon liukoisuus valituilla pH-arvoilla eri lämpötiloissa. Lisäksi seurattiin puolipanostoimisen saostuksen aikana 1-litraisella laboratoriokiteyttimellä muodostuvan kiteisen polymorfiseoksen koostumusta hyödyntäen in-line Raman-spektroskopiaa. Myös liuoksen pH-muutosta seurattiin sekä liuoksen koostumusta ATR FTIR-spektroskopian (Attenuated Total Reflection Fourier Transform Infrared Spectrometer) avulla. Tutkittavina muuttujina olivat mm. sekoitusintensiteetti, sekoitintyyppi, reaktanttien (natriumglutamaatti ja rikkihappo) konsentraatiot sekä syötetyn rikkihapon syöttökohta kiteyttimessä. Työhön sisältyi 36 koetta ja osa kokeista toistettiin tulosten oikeellisuuden tarkistamiseksi. Inline-mittaustulosten verifioimiseksi kidenäytteet analysoitiin myös käyttämällä konfokaali Raman-mikroskooppia. Kidemorfologiaa tutkittiin SEM-kuvien (Scanning Eletronic Microscope) avulla. Työ osoitti, että Raman-spektroskopia on joustava ja luotettava menetelmä saostusprosessin jatkuvaan seurantaan L-glutamiinihapolla. Alhaiset lähtöainepitoisuudet tuottivat pääasiassa ¿¿muotoa, kun taas alhainen sekoitusteho edisti ß-muodon muodostumista. Syöttökohta vaikutti merkittävästi polymorfiaan. Kun rikkihapon syöttökohta oli epäideaalisesti sekoitetulla vyöhykkeellä, nousi ylikylläisyystaso korkeaksi ja päätuote oli tällöin ß-muotoa. 6-lapainen vinolapaturbiini (nousukulma 45o) ja 6-lapainen levyturbiini eivät merkittävästi poikenneet toisistaan muodostuvien polymorfien osalta.

Monitoring of crystallization processes by using infrared spectroscopy and multivariate methods

Väitöstutkimuksessa on tarkasteltuinfrapunaspektroskopian ja monimuuttujaisten aineistonkäsittelymenetelmien soveltamista kiteytysprosessin monitoroinnissa ja kidemäisen tuotteen analysoinnissa. Parhaillaan kiteytysprosessitutkimuksessa maailmanlaajuisesti tutkitaan intensiivisesti erilaisten mittausmenetelmien soveltamista kiteytysprosessin ilmiöidenjatkuvaan mittaamiseen niin nestefaasista kuin syntyvistä kiteistäkin. Lisäksi tuotteen karakterisointi on välttämätöntä tuotteen laadun varmistamiseksi. Erityisesti lääkeaineiden valmistuksessa kiinnostusta tämäntyyppiseen tutkimukseen edistää Yhdysvaltain elintarvike- ja lääkeaineviraston (FDA) prosessianalyyttisiintekniikoihin (PAT) liittyvä ohjeistus, jossa määritellään laajasti vaatimukset lääkeaineiden valmistuksessa ja tuotteen karakterisoinnissa tarvittaville mittauksille turvallisten valmistusprosessien takaamiseksi. Jäähdytyskiteytyson erityisesti lääketeollisuudessa paljon käytetty erotusmenetelmä kiinteän raakatuotteen puhdistuksessa. Menetelmässä puhdistettava kiinteä raaka-aine liuotetaan sopivaan liuottimeen suhteellisen korkeassa lämpötilassa. Puhdistettavan aineen liukoisuus käytettävään liuottimeen laskee lämpötilan laskiessa, joten systeemiä jäähdytettäessä liuenneen aineen konsentraatio prosessissa ylittää liukoisuuskonsentraation. Tällaiseen ylikylläiseen systeemiin pyrkii muodostumaan uusia kiteitä tai olemassa olevat kiteet kasvavat. Ylikylläisyys on yksi tärkeimmistä kidetuotteen laatuun vaikuttavista tekijöistä. Jäähdytyskiteytyksessä syntyvän tuotteen ominaisuuksiin voidaan vaikuttaa mm. liuottimen valinnalla, jäähdytyprofiililla ja sekoituksella. Lisäksi kiteytysprosessin käynnistymisvaihe eli ensimmäisten kiteiden muodostumishetki vaikuttaa tuotteen ominaisuuksiin. Kidemäisen tuotteen laatu määritellään kiteiden keskimääräisen koon, koko- ja muotojakaumansekä puhtauden perusteella. Lääketeollisuudessa on usein vaatimuksena, että tuote edustaa tiettyä polymorfimuotoa, mikä tarkoittaa molekyylien kykyä järjestäytyä kidehilassa usealla eri tavalla. Edellä mainitut ominaisuudet vaikuttavat tuotteen jatkokäsiteltävyyteen, kuten mm. suodattuvuuteen, jauhautuvuuteen ja tabletoitavuuteen. Lisäksi polymorfiamuodolla on vaikutusta moniin tuotteen käytettävyysominaisuuksiin, kuten esim. lääkeaineen liukenemisnopeuteen elimistössä. Väitöstyössä on tutkittu sulfatiatsolin jäähdytyskiteytystä käyttäen useita eri liuotinseoksia ja jäähdytysprofiileja sekä tarkasteltu näiden tekijöiden vaikutustatuotteen laatuominaisuuksiin. Infrapunaspektroskopia on laajalti kemian alan tutkimuksissa sovellettava menetelmä. Siinä mitataan tutkittavan näytteenmolekyylien värähtelyjen aiheuttamia spektrimuutoksia IR alueella. Tutkimuksessa prosessinaikaiset mittaukset toteutettiin in-situ reaktoriin sijoitettavalla uppoanturilla käyttäen vaimennettuun kokonaisheijastukseen (ATR) perustuvaa Fourier muunnettua infrapuna (FTIR) spektroskopiaa. Jauhemaiset näytteet mitattiin off-line diffuusioheijastukseen (DRIFT) perustuvalla FTIR spektroskopialla. Monimuuttujamenetelmillä (kemometria) voidaan useita satoja, jopa tuhansia muuttujia käsittävä spektridata jalostaa kvalitatiiviseksi (laadulliseksi) tai kvantitatiiviseksi (määrälliseksi) prosessia kuvaavaksi informaatioksi. Väitöstyössä tarkasteltiin laajasti erilaisten monimuuttujamenetelmien soveltamista mahdollisimman monipuolisen prosessia kuvaavan informaation saamiseksi mitatusta spektriaineistosta. Väitöstyön tuloksena on ehdotettu kalibrointirutiini liuenneen aineen konsentraation ja edelleen ylikylläisyystason mittaamiseksi kiteytysprosessin aikana. Kalibrointirutiinin kehittämiseen kuuluivat aineiston hyvyyden tarkastelumenetelmät, aineiston esikäsittelymenetelmät, varsinainen kalibrointimallinnus sekä mallin validointi. Näin saadaan reaaliaikaista informaatiota kiteytysprosessin ajavasta voimasta, mikä edelleen parantaa kyseisen prosessin tuntemusta ja hallittavuutta. Ylikylläisyystason vaikutuksia syntyvän kidetuotteen laatuun seurattiin usein kiteytyskokein. Työssä on esitetty myös monimuuttujaiseen tilastolliseen prosessinseurantaan perustuva menetelmä, jolla voidaan ennustaa spontaania primääristä ytimenmuodostumishetkeä mitatusta spektriaineistosta sekä mahdollisesti päätellä ydintymisessä syntyvä polymorfimuoto. Ehdotettua menetelmää hyödyntäen voidaan paitsi ennakoida kideytimien muodostumista myös havaita mahdolliset häiriötilanteet kiteytysprosessin alkuhetkillä. Syntyvää polymorfimuotoa ennustamalla voidaan havaita ei-toivotun polymorfin ydintyminen,ja mahdollisesti muuttaa kiteytyksen ohjausta halutun polymorfimuodon saavuttamiseksi. Monimuuttujamenetelmiä sovellettiin myös kiteytyspanosten välisen vaihtelun määrittämiseen mitatusta spektriaineistosta. Tämäntyyppisestä analyysistä saatua informaatiota voidaan hyödyntää kiteytysprosessien suunnittelussa ja optimoinnissa. Väitöstyössä testattiin IR spektroskopian ja erilaisten monimuuttujamenetelmien soveltuvuutta kidetuotteen polymorfikoostumuksen nopeaan määritykseen. Jauhemaisten näytteiden luokittelu eri polymorfeja sisältäviin näytteisiin voitiin tehdä käyttäen tarkoitukseen soveltuvia monimuuttujaisia luokittelumenetelmiä. Tämä tarjoaa nopean menetelmän jauhemaisen näytteen polymorfikoostumuksen karkeaan arviointiin, eli siihen mitä yksittäistä polymorfia kyseinen näyte pääasiassa sisältää. Varsinainen kvantitatiivinen analyysi, eli sen selvittäminen paljonko esim. painoprosentteina näyte sisältää eri polymorfeja, vaatii kaikki polymorfit kattavan fysikaalisen kalibrointisarjan, mikä voi olla puhtaiden polymorfien huonon saatavuuden takia hankalaa.

Measuring irregularities and surface defects from printed patterns

Quality inspection and assurance is a veryimportant step when today's products are sold to markets. As products are produced in vast quantities, the interest to automate quality inspection tasks has increased correspondingly. Quality inspection tasks usuallyrequire the detection of deficiencies, defined as irregularities in this thesis. Objects containing regular patterns appear quite frequently on certain industries and science, e.g. half-tone raster patterns in the printing industry, crystal lattice structures in solid state physics and solder joints and components in the electronics industry. In this thesis, the problem of regular patterns and irregularities is described in analytical form and three different detection methods are proposed. All the methods are based on characteristics of Fourier transform to represent regular information compactly. Fourier transform enables the separation of regular and irregular parts of an image but the three methods presented are shown to differ in generality and computational complexity. Need to detect fine and sparse details is common in quality inspection tasks, e.g., locating smallfractures in components in the electronics industry or detecting tearing from paper samples in the printing industry. In this thesis, a general definition of such details is given by defining sufficient statistical properties in the histogram domain. The analytical definition allowsa quantitative comparison of methods designed for detail detection. Based on the definition, the utilisation of existing thresholding methodsis shown to be well motivated. Comparison of thresholding methods shows that minimum error thresholding outperforms other standard methods. The results are successfully applied to a paper printability and runnability inspection setup. Missing dots from a repeating raster pattern are detected from Heliotest strips and small surface defects from IGT picking papers.

Towards desired crystalline product properties: In-situ monitoring of batch crystallization

The objective of industrial crystallization is to obtain a crystalline product which has the desired crystal size distribution, mean crystal size, crystal shape, purity, polymorphic and pseudopolymorphic form. Effective control of the product quality requires an understanding of the thermodynamics of the crystallizing system and the effects of operation parameters on the crystalline product properties. Therefore, obtaining reliable in-line information about crystal properties and supersaturation, which is the driving force of crystallization, would be very advantageous. Advanced techniques, such asRaman spectroscopy, attenuated total reflection Fourier transform infrared (ATR FTIR) spectroscopy, and in-line imaging techniques, offer great potential for obtaining reliable information during crystallization, and thus giving a better understanding of the fundamental mechanisms (nucleation and crystal growth) involved. In the present work, the relative stability of anhydrate and dihydrate carbamazepine in mixed solvents containing water and ethanol were investigated. The kinetics of the solvent mediated phase transformation of the anhydrate to hydrate in the mixed solvents was studied using an in-line Raman immersion probe. The effects of the operation parameters in terms of solvent composition, temperature and the use of certain additives on the phase transformation kineticswere explored. Comparison of the off-line measured solute concentration and the solid-phase composition measured by in-line Raman spectroscopy allowedthe identification of the fundamental processes during the phase transformation. The effects of thermodynamic and kinetic factors on the anhydrate/hydrate phase of carbamazepine crystals during cooling crystallization were also investigated. The effect of certain additives on the batch cooling crystallization of potassium dihydrogen phosphate (KDP) wasinvestigated. The crystal growth rate of a certain crystal face was determined from images taken with an in-line video microscope. An in-line image processing method was developed to characterize the size and shape of thecrystals. An ATR FTIR and a laser reflection particle size analyzer were used to study the effects of cooling modes and seeding parameters onthe final crystal size distribution of an organic compound C15. Based on the obtained results, an operation condition was proposed which gives improved product property in terms of increased mean crystal size and narrowersize distribution.

Measurement Problems and Problem-Solving in Kraft Pulping

Tämän työn tarkoituksena on koota yhteen selluprosessin mittausongelmat ja mahdolliset mittaustekniikat ongelmien ratkaisemiseksi. Pääpaino on online-mittaustekniikoissa. Työ koostuu kolmesta osasta. Ensimmäinen osa on kirjallisuustyö, jossa esitellään nykyaikaisen selluprosessin perusmittaukset ja säätötarpeet. Mukana on koko kuitulinja puunkäsittelystä valkaisuun ja kemikaalikierto: haihduttamo, soodakattila, kaustistamo ja meesauuni. Toisessa osassa mittausongelmat ja mahdolliset mittaustekniikat on koottu yhteen ”tiekartaksi”. Tiedot on koottu vierailemalla kolmella suomalaisella sellutehtaalla ja haastattelemalla laitetekniikka- ja mittaustekniikka-asiantuntijoita. Prosessikemian paremmalle ymmärtämiselle näyttää haastattelun perusteella olevan tarvetta, minkä vuoksi konsentraatiomittaukset on valittu jatkotutkimuskohteeksi. Viimeisessä osassa esitellään mahdollisia mittaustekniikoita konsentraatiomittausten ratkaisemiseksi. Valitut tekniikat ovat lähi-infrapunatekniikka (NIR), fourier-muunnosinfrapunatekniikka (FTIR), online-kapillaarielektroforeesi (CE) ja laserindusoitu plasmaemissiospektroskopia (LIPS). Kaikkia tekniikoita voi käyttää online-kytkettyinä prosessikehitystyökaluina. Kehityskustannukset on arvioitu säätöön kytketylle online-laitteelle. Kehityskustannukset vaihtelevat nollasta miestyövuodesta FTIR-tekniikalle viiteen miestyövuoteen CE-laitteelle; kehityskustannukset riippuvat tekniikan kehitysasteesta ja valmiusasteesta tietyn ongelman ratkaisuun. Työn viimeisessä osassa arvioidaan myös yhden mittausongelman – pesuhäviömittauksen – ratkaisemisen teknis-taloudellista kannattavuutta. Ligniinipitoisuus kuvaisi nykyisiä mittauksia paremmin todellista pesuhäviötä. Nykyään mitataan joko natrium- tai COD-pesuhäviötä. Ligniinipitoisuutta voidaan mitata UV-absorptiotekniikalla. Myös CE-laitetta voitaisiin käyttää pesuhäviön mittauksessa ainakin prosessikehitysvaiheessa. Taloudellinen tarkastelu pohjautuu moniin yksinkertaistuksiin ja se ei sovellu suoraan investointipäätösten tueksi. Parempi mittaus- ja säätöjärjestelmä voisi vakauttaa pesemön ajoa. Investointi ajoa vakauttavaan järjestelmään on kannattavaa, jos todellinen ajotilanne on tarpeeksi kaukana kustannusminimistä tai jos pesurin ajo heilahtelee eli pesuhäviön keskihajonta on suuri. 50 000 € maksavalle mittaus- ja säätöjärjestelmälle saadaan alle 0,5 vuoden takaisinmaksuaika epävakaassa ajossa, jos COD-pesuhäviön vaihteluväli on 5,2 – 11,6 kg/odt asetusarvon ollessa 8,4 kg/odt. Laimennuskerroin vaihtelee tällöin välillä 1,7 – 3,6 m3/odt asetusarvon ollessa 2,5 m3/odt.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Analysis of outliers in electricity spot prices with exampleof New England and New Zealand markets

Electricity spot prices have always been a demanding data set for time series analysis, mostly because of the non-storability of electricity. This feature, making electric power unlike the other commodities, causes outstanding price spikes. Moreover, the last several years in financial world seem to show that ’spiky’ behaviour of time series is no longer an exception, but rather a regular phenomenon. The purpose of this paper is to seek patterns and relations within electricity price outliers and verify how they affect the overall statistics of the data. For the study techniques like classical Box-Jenkins approach, series DFT smoothing and GARCH models are used. The results obtained for two geographically different price series show that patterns in outliers’ occurrence are not straightforward. Additionally, there seems to be no rule that would predict the appearance of a spike from volatility, while the reverse effect is quite prominent. It is concluded that spikes cannot be predicted based only on the price series; probably some geographical and meteorological variables need to be included in modeling.

New Distance Transforms for Gray Level Image Compression

This thesis deals with distance transforms which are a fundamental issue in image processing and computer vision. In this thesis, two new distance transforms for gray level images are presented. As a new application for distance transforms, they are applied to gray level image compression. The new distance transforms are both new extensions of the well known distance transform algorithm developed by Rosenfeld, Pfaltz and Lay. With some modification their algorithm which calculates a distance transform on binary images with a chosen kernel has been made to calculate a chessboard like distance transform with integer numbers (DTOCS) and a real value distance transform (EDTOCS) on gray level images. Both distance transforms, the DTOCS and EDTOCS, require only two passes over the graylevel image and are extremely simple to implement. Only two image buffers are needed: The original gray level image and the binary image which defines the region(s) of calculation. No other image buffers are needed even if more than one iteration round is performed. For large neighborhoods and complicated images the two pass distance algorithm has to be applied to the image more than once, typically 3 10 times. Different types of kernels can be adopted. It is important to notice that no other existing transform calculates the same kind of distance map as the DTOCS. All the other gray weighted distance function, GRAYMAT etc. algorithms find the minimum path joining two points by the smallest sum of gray levels or weighting the distance values directly by the gray levels in some manner. The DTOCS does not weight them that way. The DTOCS gives a weighted version of the chessboard distance map. The weights are not constant, but gray value differences of the original image. The difference between the DTOCS map and other distance transforms for gray level images is shown. The difference between the DTOCS and EDTOCS is that the EDTOCS calculates these gray level differences in a different way. It propagates local Euclidean distances inside a kernel. Analytical derivations of some results concerning the DTOCS and the EDTOCS are presented. Commonly distance transforms are used for feature extraction in pattern recognition and learning. Their use in image compression is very rare. This thesis introduces a new application area for distance transforms. Three new image compression algorithms based on the DTOCS and one based on the EDTOCS are presented. Control points, i.e. points that are considered fundamental for the reconstruction of the image, are selected from the gray level image using the DTOCS and the EDTOCS. The first group of methods select the maximas of the distance image to new control points and the second group of methods compare the DTOCS distance to binary image chessboard distance. The effect of applying threshold masks of different sizes along the threshold boundaries is studied. The time complexity of the compression algorithms is analyzed both analytically and experimentally. It is shown that the time complexity of the algorithms is independent of the number of control points, i.e. the compression ratio. Also a new morphological image decompression scheme is presented, the 8 kernels' method. Several decompressed images are presented. The best results are obtained using the Delaunay triangulation. The obtained image quality equals that of the DCT images with a 4 x 4

Sampling in chemical analysis

The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

Simulating the performance of paper machine control

The topic of this thesis is the simulation of a combination of several control and data assimilation methods, meant to be used for controlling the quality of paper in a paper machine. Paper making is a very complex process and the information obtained from the web is sparse. A paper web scanner can only measure a zig zag path on the web. An assimilation method is needed to process estimates for Machine Direction (MD) and Cross Direction (CD) profiles of the web. Quality control is based on these measurements. There is an increasing need for intelligent methods to assist in data assimilation. The target of this thesis is to study how such intelligent assimilation methods are affecting paper web quality. This work is based on a paper web simulator, which has been developed in the TEKES funded MASI NoTes project. The simulator is a valuable tool in comparing different assimilation methods. The thesis contains the comparison of four different assimilation methods. These data assimilation methods are a first order Bayesian model estimator, an ARMA model based on a higher order Bayesian estimator, a Fourier transform based Kalman filter estimator and a simple block estimator. The last one can be considered to be close to current operational methods. From these methods Bayesian, ARMA and Kalman all seem to have advantages over the commercial one. The Kalman and ARMA estimators seems to be best in overall performance.

Supersaturation-controlled crystallization

Identification of product requirements and quality, together with the management of production are key issues in chemical engineering. Quality control of crystalline products is part of the quality of many industrially manufactured products like paper, paintings, medicines and fertilizers. In most crystallization cases, quality is described with the size, polymorph, shape and purity of the crystal. The chemical composition, hydrodynamics and driving force, together with the operating temperature are in a key position when the properties of a crystalline product are controlled with the crystallization process. This study concentrates on managing the identified properties of a crystalline product with the control of a driving force. The controlling of the driving force can be based on the change of solubility or the change of concentration. Solubility can be changed with temperature, pressure and an antisolvent. The concentration of crystallizing compound, the solute can be changed with the evaporation of the solvent and with the addition of a reagent. The present study focuses on reagent addition and temperature change as methods of changing the level of the driving force. Three control structures for direct control of supersaturation are built, one for cooling crystallization and two for reactive crystallization. Closed loop feedback control structures are based on the measurement of the solute concentration with attenuated total reflection - Fourier transform infrared spectrometer. The details of the reagent feed are analyzed with experimental studies and with results of computational fluid dynamic simulations of the inert particle pulse in the premixer and inert particle injection to the mixing tank. Nucleation in conditions of controlled reactive crystallization is analyzed with Nielsen’s equation of homogeneous nucleation. The resulting control systems, based on regulation of supersaturation, can be used to produce the desired polymorph of an organic product. The polymorph composition of product crystals is controlled repeatably with the decision of a set value of supersaturation level.

Cuticular and Suberin Polymers of Edible Plants. Analysis by Gas Chromatographic-Mass Spectrometric and Solid State Spectroscopic Methods

Cutin and suberin are structural and protective polymers of plant surfaces. The epidermal cells of the aerial parts of plants are covered with an extracellular cuticular layer, which consists of polyester cutin, highly resistant cutan, cuticular waxes and polysaccharides which link the layer to the epidermal cells. A similar protective layer is formed by a polyaromatic-polyaliphatic biopolymer suberin, which is present particularly in the cell walls of the phellem layer of periderm of the underground parts of plants (e.g. roots and tubers) and the bark of trees. In addition, suberization is also a major factor in wound healing and wound periderm formation regardless of the plants’ tissue. Knowledge of the composition and functions of cuticular and suberin polymers is important for understanding the physiological properties for the plants and for nutritional quality when these plants are consumed as foods. The aims of the practical work were to assess the chemical composition of cuticular polymers of several northern berries and seeds and suberin of two varieties of potatoes. Cutin and suberin were studied as isolated polymers and further after depolymerization as soluble monomers and solid residues. Chemical and enzymatic depolymerization techniques were compared and a new chemical depolymerization method was developed. Gas chromatographic analysis with mass spectrometric detection (GC-MS) was used to assess the monomer compositions. Polymer investigations were conducted with solid state carbon-13 cross polarization magic angle spinning nuclear magnetic resonance spectroscopy (13C CP-MAS NMR), Fourier transform infrared spectroscopy (FTIR) and microscopic analysis. Furthermore, the development of suberin over one year of post-harvest storage was investigated and the cuticular layers from berries grown in the North and South of Finland were compared. The results show that the amounts of isolated cuticular layers and cutin monomers, as well as monomeric compositions vary greatly between the berries. The monomer composition of seeds was found to differ from the corresponding berry peel monomers. The berry cutin monomers were composed mostly of long-chain aliphatic ω-hydroxy acids, with various mid-chain functionalities (double-bonds, epoxy, hydroxy and keto groups). Substituted α,ω-diacids predominated over ω-hydroxy acids in potato suberin monomers and slight differences were found between the varieties. The newly-developed closed tube chemical method was found to be suitable for cutin and suberin analysis and preferred over the solvent-consuming and laborious reflux method. Enzymatic hydrolysis with cutinase was less effective than chemical methanolysis and showed specificity towards α,ω-diacid bonds. According to ₁₃C CP-MAS NMR and FTIR, the depolymerization residues contained significant amounts of aromatic structures, polysaccharides and possible cutan-type aliphatic moieties. Cultivation location seems to have effect on cuticular composition. The materials studied contained significant amounts of different types of biopolymers that could be utilized for several purposes with or without further processing. The importance of the so-called waste material from industrial processes of berries and potatoes as a source of either dietary fiber or specialty chemicals should be further investigated in detail. The evident impact of cuticular and suberin polymers, among other fiber components, on human health should be investigated in clinical trials. These by-product materials may be used as value-added fiber fractions in the food industry and as raw materials for specialty chemicals such as lubricants and emulsifiers, or as building blocks for novel polymers.