Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

Application of multivariate statistical process control to fuel cell manufacturing

Univariate statistical control charts, such as the Shewhart chart, do not satisfy the requirements for process monitoring on a high volume automated fuel cell manufacturing line. This is because of the number of variables that require monitoring. The risk of elevated false alarms, due to the nature of the process being high volume, can present problems if univariate methods are used. Multivariate statistical methods are discussed as an alternative for process monitoring and control. The research presented is conducted on a manufacturing line which evaluates the performance of a fuel cell. It has three stages of production assembly that contribute to the final end product performance. The product performance is assessed by power and energy measurements, taken at various time points throughout the discharge testing of the fuel cell. The literature review performed on these multivariate techniques are evaluated using individual and batch observations. Modern techniques using multivariate control charts on Hotellings T2 are compared to other multivariate methods, such as Principal Components Analysis (PCA). The latter, PCA, was identified as the most suitable method. Control charts such as, scores, T2 and DModX charts, are constructed from the PCA model. Diagnostic procedures, using Contribution plots, for out of control points that are detected using these control charts, are also discussed. These plots enable the investigator to perform root cause analysis. Multivariate batch techniques are compared to individual observations typically seen on continuous processes. Recommendations, for the introduction of multivariate techniques that would be appropriate for most high volume processes, are also covered.

Multivariate Statistical Process Control and Case-Based Reasoning for situation assessment of Sequencing Batch Reactors

ABSRACT This thesis focuses on the monitoring, fault detection and diagnosis of Wastewater Treatment Plants (WWTP), which are important fields of research for a wide range of engineering disciplines. The main objective is to evaluate and apply a novel artificial intelligent methodology based on situation assessment for monitoring and diagnosis of Sequencing Batch Reactor (SBR) operation. To this end, Multivariate Statistical Process Control (MSPC) in combination with Case-Based Reasoning (CBR) methodology was developed, which was evaluated on three different SBR (pilot and lab-scales) plants and validated on BSM1 plant layout.

Deep-hole drilling process, monitoring system and sensors modifications

 In the drilling processes and especially deep-hole drilling process, the monitoring system and having control on mechanical parameters (e.g. Force, Torque,Vibration and Acoustic emission) are essential. The main focus of this thesis work is to study the characteristics of deep-hole drilling process, and optimize the monitoring system for controlling the process. The vibration is considered as a major defect area of the deep-hole drilling process which often leads to breakage of the drill, therefore by vibration analysis and optimizing the workpiecefixture, this area is studied by finite element method and the suggestions are explained. By study on a present monitoring system, and searching on the new sensor products, the modifications and recommendations are suggested for optimize the present monitoring system for excellent performance in deep-hole drilling process research and measurements.

Flow injection analysis of ethyl xanthate by gas diffusion and UV detection as CS(2) for process monitoring of sulfide ore flotation

A sensitive and robust analytical method for spectrophotometric determination of ethyl xanthate, CH(3)CH(2)OCS(2)(-) at trace concentrations in pulp solutions from froth flotation process is proposed. The analytical method is based on the decomposition of ethyl xanthate. EtX(-), with 2.0 mol L(-1) HCl generating ethanol and carbon disulfide. CS(2). A gas diffusion cell assures that only the volatile compounds diffuse through a PTFE membrane towards an acceptor stream of deionized water, thus avoiding the interferences of non-volatile compounds and suspended particles. The CS(2) is selectively detected by UV absorbance at 206 nm (epsilon = 65,000 L mol(-1) cm(-1)). The measured absorbance is directly proportional to EtX(-) concentration present in the sample solutions. The Beer`s law is obeyed in a 1 x 10(-6) to 2 x 10(-4) mol L(-1) concentration range of ethyl xanthate in the pulp with an excellent correlation coefficient (r = 0.999) and a detection limit of 3.1 x 10(-7) mol L(-1), corresponding to 38 mu g L. At flow rates of 200 mu L min(-1) of the donor stream and 100 mu L min(-1) of the acceptor channel a sampling rate of 15 injections per hour could be achieved with RSD < 2.3% (n = 10, 300 mu L injections of 1 x 10(-5) mol L(-1) EtX(-)). Two practical applications demonstrate the versatility of the FIA method: (i) evaluation the free EtX(-) concentration during a laboratory study of the EtX(-) adsorption capacity on pulverized sulfide ore (pyrite) and (ii) monitoring of EtX(-) at different stages (from starting load to washing effluents) of a flotation pilot plant processing a Cu-Zn sulfide ore. (C) 2010 Elsevier By. All rights reserved.

Grinding process monitoring based on electromechanical impedance measurements

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Process Monitoring and Defect Detection of Additive Manufacturing Using Inline Coherent Imaging

With applications ranging from aerospace to biomedicine, additive manufacturing (AM) has been revolutionizing the manufacturing industry. The ability of additive techniques, such as selective laser melting (SLM), to create fully functional, geometrically complex, and unique parts out of high strength materials is of great interest. Unfortunately, despite numerous advantages afforded by this technology, its widespread adoption is hindered by a lack of on-line, real time feedback control and quality assurance techniques. In this thesis, inline coherent imaging (ICI), a broadband, spatially coherent imaging technique, is used to observe the SLM process in 15 - 45 $\mu m$ 316L stainless steel. Imaging of both single and multilayer builds is performed at a rate of 200 $kHz$, with a resolution of tens of microns, and a high dynamic range rendering it impervious to blinding from the process beam. This allows imaging before, during, and after laser processing to observe changes in the morphology and stability of the melt. Galvanometer-based scanning of the imaging beam relative to the process beam during the creation of single tracks is used to gain a unique perspective of the SLM process that has been so far unobservable by other monitoring techniques. Single track processing is also used to investigate the possibility of a preliminary feedback control parameter based on the process beam power, through imaging with both coaxial and 100 $\mu m$ offset alignment with respect to the process beam. The 100 $\mu m$ offset improved imaging by increasing the number of bright A-lines (i.e. with signal greater than the 10 $dB$ noise floor) by 300\%. The overlap between adjacent tracks in a single layer is imaged to detect characteristic fault signatures. Full multilayer builds are carried out and the resultant ICI images are used to detect defects in the finished part and improve upon the initial design of the build system. Damage to the recoater blade is assessed using powder layer scans acquired during a 3D build. The ability of ICI to monitor SLM processes at such high rates with high resolution offers extraordinary potential for future advances in on-line feedback control of additive manufacturing.

Optical emission spectroscopy as a process-monitoring tool in PECVD of amorphous carbon coatings

Dans ce projet de recherche, le dépôt des couches minces de carbone amorphe (généralement connu sous le nom de DLC pour Diamond-Like Carbon en anglais) par un procédé de dépôt chimique en phase vapeur assisté par plasma (ou PECVD pour Plasma Enhanced Chemical Vapor deposition en anglais) a été étudié en utilisant la Spectroscopie d’Émission Optique (OES) et l’analyse partielle par régression des moindres carrés (PLSR). L’objectif de ce mémoire est d’établir un modèle statistique pour prévoir les propriétés des revêtements DLC selon les paramètres du procédé de déposition ou selon les données acquises par OES. Deux séries d’analyse PLSR ont été réalisées. La première examine la corrélation entre les paramètres du procédé et les caractéristiques du plasma pour obtenir une meilleure compréhension du processus de dépôt. La deuxième série montre le potentiel de la technique d’OES comme outil de surveillance du procédé et de prédiction des propriétés de la couche déposée. Les résultats montrent que la prédiction des propriétés des revêtements DLC qui était possible jusqu’à maintenant en se basant sur les paramètres du procédé (la pression, la puissance, et le mode du plasma), serait envisageable désormais grâce aux informations obtenues par OES du plasma (particulièrement les indices qui sont reliées aux concentrations des espèces dans le plasma). En effet, les données obtenues par OES peuvent être utilisées pour surveiller directement le processus de dépôt plutôt que faire une étude complète de l’effet des paramètres du processus, ceux-ci étant strictement reliés au réacteur plasma et étant variables d’un laboratoire à l’autre. La perspective de l’application d’un modèle PLSR intégrant les données de l’OES est aussi démontrée dans cette recherche afin d’élaborer et surveiller un dépôt avec une structure graduelle.

Multivariate monitoring of a biological wastewater treatment process: a case study at Melbourne Water's Western Treatment Plant

Biological wastewater treatment is a complex, multivariate process, in which a number of physical and biological processes occur simultaneously. In this study, principal component analysis (PCA) and parallel factor analysis (PARAFAC) were used to profile and characterise Lagoon 115E, a multistage biological lagoon treatment system at Melbourne Water's Western Treatment Plant (WTP) in Melbourne, Australia. In this study, the objective was to increase our understanding of the multivariate processes taking place in the lagoon. The data used in the study span a 7-year period during which samples were collected as often as weekly from the ponds of Lagoon 115E and subjected to analysis. The resulting database, involving 19 chemical and physical variables, was studied using the multivariate data analysis methods PCA and PARAFAC. With these methods, alterations in the state of the wastewater due to intrinsic and extrinsic factors could be discerned. The methods were effective in illustrating and visually representing the complex purification stages and cyclic changes occurring along the lagoon system. The two methods proved complementary, with each having its own beneficial features. (C) 2003 Elsevier B.V. All rights reserved.

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.

Spectrometrical Monitoring of Laser Sintering Process of Ceramic Material

This thesis is done as a part of project called FuncMama that is a project between Technical Research Centre of Finland (VTT), Oulu University (OY), Lappeenranta University of Technology (LUT) and Finnish industrial partners. Main goal of the project is to manufacture electric and mechanical components from mixed materials using laser sintering. Aim of this study was to create laser sintered pieces from ceramic material and monitor the sintering event by using spectrometer. Spectrometer is a device which is capable to record intensity of different wavelengths in relation with time. In this study the monitoring of laser sintering was captured with the equipment which consists of Ocean Optics spectrometer, optical fiber and optical lens (detector head). Light from the sintering process hit first to the lens system which guides the light in to the optical fibre. Optical fibre transmits the light from the sintering process to the spectrometer where wavelengths intensity level information is detected. The optical lens of the spectrometer was rigidly set and did not move along with the laser beam. Data which was collected with spectrometer from the laser sintering process was converted with Excel spreadsheet program for result’s evaluation. Laser equipment used was IPG Photonics pulse fibre laser. Laser parameters were kept mainly constant during experimental part and only sintering speed was changed. That way it was possible to find differences in the monitoring results without fear of too many parameters mixing together and affecting to the conclusions. Parts which were sintered had one layer and size of 5 x 5 mm. Material was CT2000 – tape manufactured by Heraeus which was later on post processed to powder. Monitoring of different sintering speeds was tested by using CT2000 reference powder. Moreover tests how different materials effect to the process monitoring were done by adding foreign powder Du Pont 951 which had suffered in re-grinding and which was more reactive than CT2000. By adding foreign material it simulates situation where two materials are accidently mixed together and it was studied if that can be seen with the spectrometer. It was concluded in this study that with the spectrometer it is possible to detect changes between different laser sintering speeds. When the sintering speed is lowered the intensity level of light is higher from the process. This is a result of higher temperature at the sintering spot and that can be noticed with the spectrometer. That indicates it could be possible to use spectrometer as a tool for process observation and support the idea of having system that can help setting up the process parameter window. Also important conclusion was how well the adding of foreign material could be seen with the spectrometer. When second material was added a significant intensity level raise could be noticed in that part where foreign material was mixed. That indicates it is possible to see if there are any variations in the material or if there are more materials mixed together. Spectrometric monitoring of laser sintering could be useful tool for process window observation and temperature controlling of the sintering process. For example if the process window for specific material is experimentally determined to get wanted properties and satisfying sintering speed. It is possible if the data is constantly recorded that the results can show faults in the part texture between layers. Changes between the monitoring data and the experimentally determined values can then indicate changes in the material being generated by material faults or by wrong process parameters. The results of this study show that spectrometer could be one possible tool for monitoring. But to get in that point where this all can be made possible much more researching is needed.

In-process thermal damage detection in grinding with monitoring via Internet

This work aims the development of a dedicated system for detection of burning in surface grinding process, where the process will constantly be monitored through the acoustic emission and electric power of the induction motor drive. Acquired by an analog-digital converter, algorithms process the signals and a control signal is generated to inform the operator or interrupt the process in case of burning occurrence. Moreover, the system makes possible the process monitoring via Internet. Additionally, a comparative study between parameters DPO and FKS is carried through. In the experimental work one type of. steel (ABNT-1020 annealed) and one type of grinding wheel referred to as TARGA, model ART 3TG80.3 NVHB, were employed.

Monitoring in precision metal drilling process using multi-sensors and neural network

This paper presents a new method to estimate hole diameters and surface roughness in precision drilling processes, using coupons taken from a sandwich plate composed of a titanium alloy plate (Ti6Al4V) glued onto an aluminum alloy plate (AA 2024T3). The proposed method uses signals acquired during the cutting process by a multisensor system installed on the machine tool. These signals are mathematically treated and then used as input for an artificial neural network. After training, the neural network system is qualified to estimate the surface roughness and hole diameter based on the signals and cutting process parameters. To evaluate the system, the estimated data were compared with experimental measurements and the errors were calculated. The results proved the efficiency of the proposed method, which yielded very low or even negligible errors of the tolerances used in most industrial drilling processes. This pioneering method opens up a new field of research, showing a promising potential for development and application as an alternative monitoring method for drilling processes. © 2012 Springer-Verlag London Limited.