Diss. (sammanfattning) Umeå : Umeå univ., 2006. / Härtill 4 uppsatser.

Diss. (sammanfattning) Umeå : Umeå universitet, 2006. / Härtill 5 uppsatser.

Vid kemisk massatillverkning finns behov av mättekniker som möjliggör ytterligare optimering av processen. Möjligheten att analysera svartlut med hjälp av aktiv akustisk spektrometri utreddes genom att ett online instrument konstruerdes och installerdes på ett pappersbruk. Analyser med multivariata metoder utfördes på resultaten. På grund av yttre omständigheter försenades arbetet, och ett tillräckligt dataunderlag för en definitiv slutsats erhölls ej. En rad vidare arbeten föreslås. / There is a need for additional process monitoring techniques in the production of chemical pulp. The possibility of analyzing black liquor by active acoustic spectrometry was investigated by constructing an on-line instrument and installing it in a chemical pulp mill. The results were then analyzed with multivariate methods. Due to unforeseen delays a sufficient amount of data could not be collected, and therefore a definitive conclusion could not be reached. Further work is suggested.

The purpose of this thesis is to evaluate the combination of bibliographic coupling and three hierarchical cluster analytic techniques: average, complete and single linkage. Bibliographic coupling is applied as a measure of similarity between recently published articles and the cluster techniques are used for the partition of a set of articles into subsets of articles with similar research focus. The field of information science is applied as the test arena and the selection of data, i.e., the article population to be partitioned, is based on a number of central journals. Methods of evaluation include both quantitative approaches as well as a qualitative one. For comparing the resulting partitions, adjusted Rand index is utilized and for the establishment of cluster coherence and isolation, measures of average normalized coupling strength is applied. In an effort to quantify the degree of subject focus within clusters, normalized entropy of a cluster’s distribution of weighted descriptors is calculated. Manual inspection of cluster composition is also performed. The findings show that choice of cluster method has a profound impact on the resulting partitions. Complete linkage generated highly subject coherent clusters but produced a fragmented picture of the research field in question, i.e., the split up of research specialties. Single linkage on the other hand, performed unsatisfactory and is not recommended. It is suggested that average linkage, when combined with a stopping rule (the inconsistency coefficient), should be considered as the method of choice since it mainly generated reasonable subject coherent clusters while avoiding severe fragmentation. / Uppsatsnivå: D

Traditionell mätteknik innebär att instrument monteras i rör eller på andra sätt förs in i processen. Detta kan vara problematiskt vid svårhanterliga processfluider och i vissa fall ge missvisande analysresultat. Tekniken Aktiv Akustisk Spektroskopi, som bygger på att mäta en utsänd ljudsignals dämpning genom processfluider, kan dock kringgå detta. Mätinstrumentet med denna teknik kallas för Acospector och marknadsförs av företaget Acosense. Instrumentet är helt beröringsfritt och kan installeras och underhållas utan processtopp. Genom multivariat analys av ljudspektrum från instrumentet fås information om processen, fluiden och dess fysikaliska egenskaper så som viskositet, koncentration, torrsubstans, densitet m.m.   Projektet ”Realtidsanalys av kiselsol” genomfördes under 10 veckor som en del av Acosenses utvecklingsarbete för nya användningsområden för Acospector. Projektet utredde möjligheten till realtidsanalys av specifik yta för kiselsol vid en ny mätposition hos Akzo Nobel Pulp Performance Chemicals (tidigare Eka Chemicals).   Projektet har haft som mål att validera Acosense teknik för den nya mätpositionen mot den fysikaliska egenskapen specifik yta. Detta skulle göras genom att ta fram ett så bra kalibreringsunderlag som möjligt och skapa en kalibrerad modell som kan prediktera egenskaper hos ett valideringsset. Ett annat mål var även att granska befintliga laborationsmetoder hos Akzo Nobel för specifik yta.   Arbetet bestod till stor del av att samla in kalibreringsprover som analyserades med avseende på specifik yta, pH, Na2O-halt, turbiditet, densitet, viskositet och konduktivitet. För proverna erhölls även spektrum som behandlades med Direct Fourier Transform och analyserades samt korrelerades med laborationsresultaten med hjälp av multivariat analys.    Viktiga parametrar för att få så jämförbara resultat för specifik yta som möjligt är noggrant och konsekvent utförda laborationsanalyser, pH-elektrodens känslighet och tiden från det att prov tagits ut till dess att analys utförs. Granskning av Akzo Nobels laborationsmetoder gav inga konkreta förslag på förändringar i laborationsinstruktionen, även om projektets och fabriksoperatörers resultat skilde sig åt.     Resultaten från multivariat analys av spektrumen och laborationsresultaten visade efter den initiala valideringen med befintlig data ge en bra modell för att mäta specifik yta. Arbetet med att få fram modellen, genomfördes genom att börja med att identifiera ett fåtal observationer som avvek från övriga. De kunde efter fortsatt granskning uteslutas. Rekommendation är att genomföra ytterligare validering av modellen med ett externt dataset. När ett sådant test är gjort skulle det kunna bevisas hur applicerbar framtagen modell är för applikationen realtidsanalys av specifik yta hos kiselsol.   Inför nya installationer av Acospectorn verkar liknade projekt med riktade punktinsatser för insamling av större mängd laborationsprover genomförda på samma sätt, vara ett bra sätt att kunna säkerställa ett kalibreringsunderlag med bra kvalitet. Noggrant utförda analyser och bra analysmetoder begränsar spridningen i resultaten vilket kan ge bra resultat under en kort tidsperiod. / Traditional measurement techniques are often conducted by mounting instruments inside pipes or are in other ways introducing them to the process. This can be problematic when handling process fluids that are dangerous, cause precipitations or are in other ways hard to handle and might give misleading results. One way to avoid these problems are using the measuring technique Active Acoustic Spectroscopy. Active Acoustic Spectroscopy is conducted by measuring sound signals attenuation through process fluids. The instrument for this is called Acospector and is produced and marketed by the company Acosense. The Acospector is noninvasive and can be installed and maintained without needing to stop the manufacturing process. Through multivariate data analysis of the spectrums from the instrument, vital information is revealed about the process.   The project “Real Time Analysis of Silica Sol” was conducted during 10 weeks as a part of Acosense development plan for new application areas. The project evaluated the possibility of real time analysis of specific surface of silica sol at a new position at Akzo Nobel Pulp & Performance Chemicals (former known as Eka Chemicals).   The objective of the project was to validate Acosense technique for the new position and specific surface. This was to be done by collecting as good calibration data as possible and create a model which could predict properties of a validation data set. Another objective was to evaluate Akzo Nobel’s lab methods for analyzing specific surface.   A large part of the work was to collect calibration samples from the process and analyze them for specific surface, pH, Na2O-content, turbidity, density, viscosity and conductivity. A spectrum was also collected for each calibration sample with the Acospector. These spectrums were then treated with Direct Fourier Transform and analyzed and correlated with lab results by multivariate data analysis.   Important parameters for comparable results are carefully and consistent conducted analysis, the pH-electrodes sensitivity and the time that passes between the out take of the sample and analysis. Evaluation of Akzo Nobel’s lab methods for specific surface gave no suggestions to changes in the lab instruction even though the projects results and factory operators’ results deviated.   The results from the multivariate analysis of the spectrums and lab results showed after an initial validation with collected data to give a good model for prediction of specific surface. The work to develop the model was done by identifying some observations that deviated from the others. These could after further review be excluded from the data set. It is recommended to conduct further validation of the model with a new data set that hasn’t been used to build the model. When this is done, it would be proved how useful the model is for the application of real time analysis of specific surface at Akzo Nobel.    For new installations of the Acospector similar projects, with targeted operations for collecting large amounts of lab samples conducted in the same way, seems to be a good way to ensure good quality of the calibration data. Thoroughly and consistent conducted analyzing methods are crucial to limit the error in the calibration data and produce good results during a short period of time.

<p> </p><p>The today quarry planning at Klinthagen is rough, which provides an opportunity to introduce new exciting methods to improve the quarry gain and efficiency. Nordkalk AB, active at Klinthagen, wishes to start a new quarry at a nearby location. To exploit future quarries in an efficient manner and ensure production quality, multivariate statistics may help gather important information.</p><p>In this thesis the possibilities of the multivariate statistical approaches of Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression were evaluated on the Klinthagen bore data. PCA data were spatially interpolated by Kriging, which also was evaluated and compared to IDW interpolation.</p><p>Principal component analysis supplied an overview of the variables relations, but also visualised the problems involved when linking geophysical data to geochemical data and the inaccuracy introduced by lacking data quality.</p><p>The PLS regression further emphasised the geochemical-geophysical problems, but also showed good precision when applied to strictly geochemical data.</p><p>Spatial interpolation by Kriging did not result in significantly better approximations than the less complex control interpolation by IDW.</p><p>In order to improve the information content of the data when modelled by PCA, a more discrete sampling method would be advisable. The data quality may cause trouble, though with sample technique of today it was considered to be of less consequence.</p><p>Faced with a single geophysical component to be predicted from chemical variables further geophysical data need to complement existing data to achieve satisfying PLS models.</p><p>The stratified rock composure caused trouble when spatially interpolated. Further investigations should be performed to develop more suitable interpolation techniques.</p>

Varje studie av en verklig process eller ett verkligt system är baserat på mätdata. Förr var den tillgängliga datamängden vid undersökningar ytterst begränsad, men med dagens teknik är mätdata betydligt mer lättillgängligt. Från att tidigare enbart haft få och ofta osammanhängande mätningar för någon enstaka variabel, till att ha många och så gott som kontinuerliga mätningar på ett större antal variabler. Detta förändrar möjligheterna att förstå och beskriva processer avsevärt. Multivariat analys används ofta när stora datamängder med många variabler utvärderas. I det här projektet har de multivariata analysmetoderna PCA (principalkomponentanalys) och PLS (partial least squares projection to latent structures) använts på data över avloppsvatten insamlat på Hammarby Sjöstadsverk. På reningsverken ställs idag allt hårdare krav från samhället för att de ska minska sin miljöpåverkan. Med bland annat bättre processkunskaper kan systemen övervakas och styras så att resursförbrukningen minskas utan att försämra reningsgraden. Vissa variabler är lätta att mäta direkt i vattnet medan andra kräver mer omfattande laboratorieanalyser. Några parametrar i den senare kategorin som är viktiga för reningsgraden är avloppsvattnets innehåll av fosfor och kväve, vilka bland annat kräver resurser i form av kemikalier till fosforfällning och energi till luftning av det biologiska reningssteget. Halterna av dessa ämnen i inkommande vatten varierar under dygnet och är svåra att övervaka. Syftet med den här studien var att undersöka om det är möjligt att utifrån lättmätbara variabler erhålla information om de mer svårmätbara variablerna i avloppsvattnet genom att utnyttja multivariata analysmetoder för att skapa modeller över variablerna. Modellerna kallas ofta för mjukvarusensorer (soft sensors) eftersom de inte utgörs av fysiska sensorer. Mätningar på avloppsvattnet i Linje 1 gjordes under tidsperioden 11 – 15 mars 2013 på flera ställen i processen. Därefter skapades flera multivariata modeller för att försöka förklara de svårmätbara variablerna. Resultatet visar att det går att erhålla information om variablerna med PLS-modeller som bygger på mer lättillgänglig data. De framtagna modellerna fungerade bäst för att förklara inkommande kväve, men för att verkligen säkerställa modellernas riktighet bör ytterligare validering ske. / Studies of real processes are based on measured data. In the past, the amount of available data was very limited. However, with modern technology, the information which is possible to obtain from measurements is more available, which considerably alters the possibility to understand and describe processes. Multivariate analysis is often used when large datasets which contains many variables are evaluated. In this thesis, the multivariate analysis methods PCA (principal component analysis) and PLS (partial least squares projection to latent structures) has been applied to wastewater data collected at Hammarby Sjöstadsverk WWTP (wastewater treatment plant). Wastewater treatment plants are required to monitor and control their systems in order to reduce their environmental impact. With improved knowledge of the processes involved, the impact can be significantly decreased without affecting the plant efficiency. Several variables are easy to measure directly in the water, while other require extensive laboratory analysis. Some of the parameters from the latter category are the contents of phosphorus and nitrogen in the water, both of which are important for the wastewater treatment results. The concentrations of these substances in the inlet water vary during the day and are difficult to monitor properly. The purpose of this study was to investigate whether it is possible, from the more easily measured variables, to obtain information on those which require more extensive analysis. This was done by using multivariate analysis to create models attempting to explain the variation in these variables. The models are commonly referred to as soft sensors, since they don’t actually make use of any physical sensors to measure the relevant variable. Data were collected during the period of March 11 to March 15, 2013 in the wastewater at different stages of the treatment process and a number of multivariate models were created. The result shows that it is possible to obtain information about the variables with PLS models based on easy-to-measure variables. The best created model was the one explaining the concentration of nitrogen in the inlet water.

The today quarry planning at Klinthagen is rough, which provides an opportunity to introduce new exciting methods to improve the quarry gain and efficiency. Nordkalk AB, active at Klinthagen, wishes to start a new quarry at a nearby location. To exploit future quarries in an efficient manner and ensure production quality, multivariate statistics may help gather important information. In this thesis the possibilities of the multivariate statistical approaches of Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression were evaluated on the Klinthagen bore data. PCA data were spatially interpolated by Kriging, which also was evaluated and compared to IDW interpolation. Principal component analysis supplied an overview of the variables relations, but also visualised the problems involved when linking geophysical data to geochemical data and the inaccuracy introduced by lacking data quality. The PLS regression further emphasised the geochemical-geophysical problems, but also showed good precision when applied to strictly geochemical data. Spatial interpolation by Kriging did not result in significantly better approximations than the less complex control interpolation by IDW. In order to improve the information content of the data when modelled by PCA, a more discrete sampling method would be advisable. The data quality may cause trouble, though with sample technique of today it was considered to be of less consequence. Faced with a single geophysical component to be predicted from chemical variables further geophysical data need to complement existing data to achieve satisfying PLS models. The stratified rock composure caused trouble when spatially interpolated. Further investigations should be performed to develop more suitable interpolation techniques.

Panna 6 på Högdalenverket i södra Stockholm (P6) med tillhörande ångturbin producerar kraftvärme genom förbränning av utsorterat returbränsle från industri och samhälle. För att minimera underhållskostnader och öka anläggningens tillgänglighet är det viktigt att fel och oönskat processbeteende kan upptäckas i ett tidigt skede. I detta syfte testas här en metod för detektering av avvikande händelser med hjälp av principalkomponentanalys (PCA) på produktionsprocessen för kraftvärme. En PCA-modell med reducerad dimension skapas utifrån processdata från en problemfri driftperiod och används som mall för inkommande data att jämföras med i ett kontrolldigram. Avvikelser ifrån modellen bör vara en indikation på att ett onormalt drifttillstånd har uppkommit och orsaker till avvikelsen analyseras. Som avvikande händelse testas två fall av tubläckage som uppstod i ett av tubpaketen för kylning av rökgaserna under 2014 och 2015. Resultatet visar att processavvikelser ifrån normallägesmodellerna tydligt syns i kontrolldiagrammen vid båda tubläckagen och avvikelserna kan härledas till variabler som är kopplade till tubläckage. Det finns potential för att tillämpa metoden för övervakning av processen, en svårighet ligger i att skapa en modell som representerar processen när den är stabil på grund av att det finns många varierande driftfall som anses stabila, detta kräver vidare arbete. Metoden kan redan användas som analysverktyg exempelvis vid misstanke om tubläckage. / Boiler 6 at the Högdalen facility in southern Stockholm (P6) combined with a a steam turbine produces Combined Heat and Power (CHP) through combustion of treated industry waste. In order to minimise maintenance costs and increase plant availability it is of importance to detect process faults and deviations at an early state. In this study a method for outlier detection using Principal Component Analysis (PCA) is applied on the CHP production process. A PCA model with reduced dimension is created using process data from a problem free period and is used as a template for new operating data to be compared with in a control chart. Deviations from the model should be an indication of the presence of abnormal conditions and the reasons for the deviations are analysed. Two cases of tube failure in 2014 and 2015 are used to study the deviations. The result shows that process deviations from the models can be detected in the control chart in both cases of tube failure and the variables known to be associated with tube failure contributes highly to the deviating behaviour. There is potential for applying this method for process control, a difficulty lies in creating a model that represents the stable process when there are big variances within what is considererd a stable process state. The method can be used for data analysis when suspecting a tube failure.

Lake volume and lake depth are important variables that defines a lake and its ecosystem. Sweden has around 100 000 lakes, but only around 8000 lakes has measured data for volume, max- and mean-depth. To collect data for the rest of the lakes is presently too time consuming and expensive, therefore a predictive method is needed. Previous studies by Sobek et al. (2011) have found a model predicting lake volume from map-derived parameters with high degrees of explanation for mean volume of 15 lakes or more. However, the predictions for one individual lake, as well as max- and mean-depth, were not accurate enough. The purpose with this study was to derive better models based on new map material with higher resolution. Variables used was derived using GIS-based calculations and then analyzed with multivariate statistical analysis with PCA, PLS-regression and multiple linear regression. A model predicting lake volume for one individual lake with better accuracy than previous studies was found. The variables best explaining the variations in lake volume was lake area and the median slope of an individual zone around each lake (R2=0.87, p&lt;0.00001). Also, the model predicting max-depth from lake area, median slope of an individual zone around each lake and height differences in the closest area surrounding each lake, had higher degrees of explanation than in previous studies (R2=0.42). The mean-depth had no significant correlation with map-derived parameters, but showed strong correlation with max-depth. Reference Sobek, S., Nisell, J. &amp; Fölster J. (2011). Predicting the volume and depths of lakes from map-derived parameters. Inland Waters, vol. 1, ss. 177-184.