Grinding operations can be analyzed through monitoring and analysis of the spindle power during the process. Due to the complexity of the process, the analysis on grinding processing signal still heavily relies on personal experience of the engineer instead of having a standard structured method. Therefore, subjectivity and inconsistency is introduced into the analysis procedure. In this thesis, a general method is established to characterize signal, utilize the characterization result to predict the real time condition of grinding wheels and the impact on the process performance measures, and provide suggestions in modification of process parameters to improve the grinding operation. This method is initiated from signal acquisition and conducted based on characterizing the signal and organizing expert knowledge. When the standard procedure to analyze the grinding process through power signal is established, the correlation between input and output can be understood, which can later be utilized for diagnostic applications. During the diagnosis, the real-time grinding wheel status is estimated and the output of the process is predicted. Then, suggestions on modifying the input parameters to address given output issue are generated. Therefore, a signal analysis and knowledge based monitoring and diagnosing system is developed to help enhance the current grinding process planning. This system is realized with a software tool developed with specifically designed algorithms under Matlab environment, upgrading from manual signal processing to an automated characterization procedure and providing process evaluation and improvement suggestions, which will improve the objectivity, consistency and accuracy in the analysis of grinding processes.

The purpose of this research was a proof of concept using a fan motor stator as transducer to monitor motor rotor and attached axial fan for mechanical motion. The proof was to determine whether bearing faults and fan imbalances could be detected in vane-axial fans using Motor Electrical Signature Analysis (MESA). The data was statistically analyzed to determine if the MESA systems could distinguish between baseline conditions and discrete fault frequencies for the three test conditions: bearing inner race defect, bearing outer race defect, and fan imbalance. The statistical conclusions for these proofs of concept were that MESA could identify all three faulted conditions.

The analysis of logic device characterization have been performed. Logic device sorts and its characterization analysis was made. The analysis of other logic device test system was performed. The logic test system requirements was made. The hardware project of logic device test system and system hardware mounting was made. The software for the logic device test system was made. Experimentation of logic device test system was performed. The results of experimentation was given. Graphs about logic test system analysis of trustiness research was given. Performed finding about the logic device test system accordance for technical requirements, trustiness and universality.

The masters thesis is concerned with the setting of limits and criteria, the design of database environment and the evaluation of the current state of motors of the important machines related to own consumption of the Nuclear power plant Dukovany. The first part of the thesis is a short description of induction motors, the evaluation method and the inventory of the observed motors related to own consumption of Nuclear power plant Dukovany. The second part of the thesis concerns the design of limits and criteria for evaluating the current state of these important motors. Finally, the thesis shows a short description of the electro monitoring system together with the description of the database environment created. In the supplementary materials of the thesis, there is a design of a protocol template for evaluation of the current state of the motor and a technical report template for regular evaluation in monitored areas MCSA (Motor Current Signature Analysis) of the state of the induction motors.

Face aux enjeux climatiques actuels, le secteur bâtiment est encouragé à réduire sa consommation énergétique tout en préservant le confort des occupants. C’est dans ce contexte que s’inscrit le projet ANR PRECCISION qui vise au développement d’outils et de méthodes pour la gestion énergétique optimisée des bâtiments qui nécessitent l’utilisation de modèles thermiques dynamiques. Les travaux de thèse, effectués entre le G2Elab et le G-SCOP, se sont focalisés sur les problématiques liées à l’estimation paramétrique de ces modèles. En effet, les incertitudes liées aux phénomènes mal maîtrisés et la nature des modèles rendent le calibrage des paramètres des modèles délicat. Cette procédure complexe n’est à ce jour pas systématisable : les modèles auto-regressifs ont une faible capacité d'extrapolation car leur structure est inadaptée, tandis que les modèles physiques sont non-linéaires par rapport à de nombreux paramètres : les estimations conduisent à des optimums locaux fortement dépendant de l'initialisation. Pour lever ce verrou, plusieurs approches ont été explorées à partir de modèles physiques adaptés pour lesquels des études sur l’identifiabilité ont été menées sur une plateforme expérimentale : PREDIS MHI. Différentes stratégies d'optimisation sont alors proposées visant à déterminer les paramètres qui peuvent être recalés. La première approche repose sur une analyse a priori de la dispersion paramétrique, la seconde repose sur une procédure de méta-optimisation qui détermine dynamiquement, au fur et à mesure d'une séquence d'optimisations, les paramètres à recaler. Les résultats sont analysés et comparés à diverses approches (modèles universels, identification « naïve » de tous les paramètres d’un modèle physique, algorithme génétique, …) à travers différents cas d'application. / In order to tackle the actual climate issues, the building field is encouraged to reduce his energetic consumption without changing the occupant’s comfort. In this context, the aim of the ANR PRECCISION project is to develop tools and methods for energetic management of the buildings which needs the use of dynamical thermal models. The PHD works, realise between the G2Elab and the G-SCOP, was focused on models parametric estimation issues. Indeed, uncertainties due to unknown phenomena and the nature of models lead to difficulties for the calibration of the models. Nowadays, this complex procedure is still not automatable: auto-regressive models have a low capacity to extrapolate because of their inadequate structure, whereas the physical models are non-linear regarding many parameters: estimations lead towards local optimums which highly depend on the initial point. In order to eliminate these constraints, several approaches have been explored with physical models adapted for which identifiability studies have been reached on an experimental platform: PREDIS MHI. Different optimisation strategies will be proposed in order to determine the parameters which can be estimated. The first approach uses an analyse a priori of the parametric dispersion, the second one use a meta optimisation which dynamicaly determined as the optimisation sequence, the parameters which can be readjusted. The results are analysed and compared to several approaches (universal models, “simple” identification of all the parameters of a physical model, genetic algorithm …) in different application cases.

No description available.

Foreign object insertion into the vagina of a murder victim is a rare occurrence. When it is encountered it is often seen as an indicator of a sexual murder, or regarded for signature analysis purposes. Due to its rare occurrence it is often only documented in literature in case-study form. In this research seventeen cases of vaginal foreign object insertion were analysed, by far the largest study of this occurrence to date. Cases were only included in the research if the object was still in the vagina when the body was discovered. The research set out to determine the typical victim profile, crime-scene actions, and offender profile, with the intention of assisting in the profiling of these crimes in the future. There were distinct differences amongst the victims in terms of race, occupation, time of death, cause of death, circumstances and area of the crimes. Only six of the seventeen crimes had been solved, yet amongst the eight known offenders certain common characteristics were observed. / Dissertation (MA)--University of Pretoria, 2007. / Social Work and Criminology / unrestricted

Submitted by SBI Biblioteca Digital (sbi.bibliotecadigital@puc-campinas.edu.br) on 2018-04-10T12:01:51Z No. of bitstreams: 1 MARCOS AUR?LIO BEHRENS.pdf: 3872179 bytes, checksum: edb54d47e1f7953187e4e8675003302b (MD5) / Made available in DSpace on 2018-04-10T12:01:51Z (GMT). No. of bitstreams: 1 MARCOS AUR?LIO BEHRENS.pdf: 3872179 bytes, checksum: edb54d47e1f7953187e4e8675003302b (MD5) Previous issue date: 2018-02-08 / The objective of this work is to monitor the electrical equipment of a production line, aiming at monitoring in real time the state of the operation of the monitored machines, allowing the accomplishment of equipment management and early detection of operational deviations and faults. The developed system performs the measurement of the effective electric current through monitored equipment, use a network of sensors connected to a data concentrator module, which in turn performs the intermediate storage, the preliminary treatment of the data and the subsequent send an Internet platform of Things (Internet of Things - IoT). The preliminary treatment of data for analysis of the time series of values of electric currents to obtain an initial evaluation of the state of operation of the monitored machine. Then, the pre-processed information is sent via the internet, a usage platform for term storage, post-processing and real-time visualization of the data by users of interest. In the data platform, the data is formatted for visualization and evaluation of the users, allowing the presentation of alerts and knowledge when deviations are detected in relation to the normal operational parameters. When a current consumption behavior deviation is detected, correlating a potential failure type, the system signals additional information to a User's interest group (to the supervisor of the production line, for example), which in a planned manner, proceeds to some intervention without equipment, without prejudice of the production. The availability of the full-time series of stored data as well as the history of occurrences recorded throughout the use of the monitoring system but is still looking for correlations between data of other origins and nature, and the interpretation of the same data under other perspectives beyond the operation or maintenance of the machine. The monitoring system proposed in this work allows to provide a minimum of automation in old machines and opens the possibility of independent, parallel and non-intrusive monitoring in machines that already have a modern supervisory system. An industry that achieves the goal of making all its production equipment fully monitored is credited to take the next step towards Industry 4.0. / Este trabalho tem como objetivo apresentar um sistema de monitoramento de equipamentos el?tricos de uma linha de produ??o, visando o acompanhamento em tempo real do estado de opera??o das m?quinas monitoradas, permitindo a realiza??o da gest?o de opera??o desses equipamentos e a detec??o antecipada de desvios operacionais e de falhas. O sistema desenvolvido realiza a medi??o da corrente el?trica eficaz consumida pelos equipamentos monitorados, utilizando uma rede de sensores conectados a um m?dulo concentrador de dados, que por sua vez realiza o armazenamento intermedi?rio, o tratamento preliminar dos dados e o posterior envio a uma plataforma de Internet da Coisas (Internet of Things - IoT). O tratamento preliminar de dados visa ? an?lise da s?rie temporal dos valores das correntes el?tricas com o fim de obter uma avalia??o inicial do estado de opera??o da m?quina monitorada. Em seguida, essas informa??es pr?-processadas s?o enviadas via internet a uma plataforma de IoT com o objetivo de armazenamento a longo prazo, p?s-processamento e visualiza??o em tempo real dos dados pelos usu?rios de interesse. Na plataforma de IoT, os dados s?o formatados para exibi??o e avalia??o dos usu?rios considerando formatos gr?ficos compreens?veis, sendo poss?vel a emiss?o de alertas e de relat?rios ao serem detectados desvios em rela??o aos par?metros operacionais normais. Ao ser detectado um desvio de comportamento no consumo de corrente, correlacionando a algum tipo de falha em potencial, o sistema sinaliza informa??es adicionais a um usu?rio de interesse (ao supervisor da linha de produ??o, por exemplo), que de forma planejada, procede a alguma interven??o no equipamento, sem preju?zo da produ??o. A disponibilidade da s?rie temporal completa dos dados armazenados bem como o hist?rico de ocorr?ncias registrados ao longo do uso do sistema de monitoramento permite ainda a busca de correla??es entre dados de outras origens e naturezas, e a interpreta??o dos mesmos dados sob outras ?ticas em contextos al?m da opera??o ou manuten??o da m?quina. O sistema de monitoramento proposto permite prover um m?nimo de automa??o em m?quinas antigas e abre a possibilidade de monitoramento independente, paralela e n?o intrusiva em m?quinas que j? contam com um sistema supervis?rio moderno. Uma ind?stria que atinja o objetivo de tornar o conjunto de seus equipamentos produtivos totalmente monitorado se credencia para dar o pr?ximo passo rumo ? Ind?stria 4.0.

This paper concerns methods of verification of person's signature and handwriting. Some of commonly used techniques are resumed and described with related literature being referred. Next aim of this work is design and implementation of a simple handwriting verification application. Application is based on edge detection and comparison of a set of structural and statistical features. As a support classification tool a SVM classifier of the LIBSVM software is employed. The Application is written in C language using OpenCV graphics library. Testing and training set was extracted from samples found in the IAM Handwriting Database. Application was created and tested in the Windows XP operating system.

[ES] Las bombas hidráulicas son el núcleo de muchos procesos en la industria y el sector servicios. Conviene tener en cuenta que los motores eléctricos son responsables del 69% del consumo de energía eléctrica en la industria, siendo en torno a un 22% de motores utilizados para el accionamiento de bombas. Los fallos de estas bombas pueden provocar averías en el proceso y, por lo tanto, implican altos costes económicos para el operador de la planta. Además, un funcionamiento defectuoso de las bombas conlleva una reducción de la eficiencia energética de la planta. De forma habitual, se utilizan principalmente dos tipos de estrategias orientadas al mantenimiento de maquinaria. Una estrategia de mantenimiento (mantenimiento preventivo) consiste en la sustitución de las piezas desgastadas en un intervalo de tiempo fijo. Este tipo de estrategia presenta muchas desventajas asociadas a la escasa optimización en el uso de los recursos y al consiguiente impacto económico. Por otro lado, la estrategia basada en la condición del equipo (mantenimiento basado en la condición) liga el reemplazo de las piezas desgastadas al estado del equipo, el cual es monitorizado a través de señales adquiridas mediante sensores. Sin embargo, el uso de sensores tiene algunos inconvenientes, como costes de inversión adicionales, posibles problemas en el montaje del sensor y posibles fallos del mismo. El análisis de la señal de corriente no se ha utilizado de forma habitual en la práctica para evaluar el estado de la bomba, aunque en muchas aplicaciones se dispone de sensores de corriente ya instalados que se podrían utilizar a tal fin. Se ha demostrado que técnicas basadas en el análisis de la corriente resultan de gran utilidad para diagnosticar varios tipos de fallos en motores eléctricos. De hecho, el análisis de la firma de corriente del motor se utiliza hoy en día ampliamente en la industria, especialmente para el diagnóstico de fallos en motores de inducción. En la presente tesis, se evalúa la utilización de la técnica de análisis de corrientes para el diagnóstico de fallos típicos relacionados con las bombas en diferentes aplicaciones. Se investigan tres tipos de bombas diferentes: bombas en línea de rotor húmedo, bombas de rotor seco y bombas sumergibles. En la tesis se han adaptado diversas técnicas, previamente empleadas para la detección de fallos en motores, al diagnóstico de fallos en la propia bomba. Los resultados indican que fallos como obstrucción de la bomba, fisura del impulsor y desgaste de los cojinetes influyen especialmente en dos frecuencias del espectro de corriente, las cuales pueden utilizarse como base de estrategias de mantenimiento basadas en la condición. En concreto, en las bombas de rotor húmedo, estos dos indicadores de fallo varían sensiblemente en función del punto de carga hidráulica de la bomba. Con la ayuda de un método de extracción de características basado en la motor reference frame theory, se demuestra que las mencionadas frecuencias pueden analizarse en tiempo real en un entorno industrial. Además, se presentan directrices para la monitorización en la nube y se valida con la ayuda de ensayos de laboratorio. Adicionalmente, se demuestra que los fallos son también detectables al analizar la corriente de arranque mediante herramientas de descomposición tiempo-frecuencia. Este hito no se había abordado anteriormente en la literatura técnica del área en lo referente a la detección de fallos en bombas. En conclusión, los resultados de este trabajo demuestran que los métodos de diagnóstico basados en la corriente pueden detectar con éxito diversos tipos de fallo en bombas, lo cual constituye un punto de gran interés para las industrias que utilicen estos activos en sus procesos. / [CA] Les bombes hidràuliques són el nucli de molts processos en la indústria i en el sector dels serveis. Cal mencionar que els motors elèctrics són responsables del 69% del consum de la energia elèctrica en la indústria, sent al voltant del 22% dels motors utilitzats per l'accionament de bombes. Les fallades d'aquestes bombes poden causar avaries en els processos, i per tant, representen un alt cost econòmic per a l'operador de la planta. A més a més, un funcionament defectuós en les bombes representa una reducció de l'eficiència energètica de la planta. De manera habitual, s'utilitzen principalment dos tipus d'estratègies orientades al manteniment de la maquinària. Una estratègia de manteniment (manteniment preventiu) consisteix en la canvi de les peces desgastades en un interval fixe de temps. Aquest tipus d'estratègia presenta molts desavantatges associats a la reduïda optimització en el ús dels recursos i el seu impacte econòmic. D'altra banda, la estratègia basada en la condició dels equipaments (manteniment basat en la condició) enllaça la substitució de les peces desgastades al estat de l'equip, el qual es monitoritzat per mig de senyals adquirides per sensors. No obstant això, el ús de sensors té alguns inconvenients com costos d'inversió addicionals, possibles problemes al muntatge i possibles fallades. L'anàlisi dels senyals de corrent no s'utilitzen de manera habitual en la pràctica per avaluar l'estat de la bomba, encara que en moltes aplicacions, estos sensors es troben instal·lats i es podrien fer servir per a aquesta finalitat. Ha estat demostrat que les tècniques basades en l'anàlisi de la corrent són de gran utilitat per el diagnosi de diversos tipus de fallades en motors elèctrics. De fet, l'anàlisi de la firma de la corrent del motor s'utilitza àmpliament en l'indústria, especialment per el diagnosi de fallades en motors d'inducció. En la present tesi, s'avalua l'utilització de la tècnica d'anàlisi de corrents per el diagnosi de fallades típiques relacionades en bombes per a diferents aplicacions. Se investiguen tres tipus de bombes diferents: bombes en línia de rotor humit, bombes de rotor sec i bombes submergibles. En aquesta tesi se han adaptat diverses tècniques, prèviament utilitzades en el diagnosi de màquines elèctriques, per al diagnosi de la pròpia bomba. Els resultat indiquen que les fallades com obstrucció de la bomba, la fissura de l'impulsor i el desgast dels coixinets influeixen especialment en dos freqüències de l'espectre de la corrent, les quals es poden utilitzar com a base per a una estratègia de manteniment basada en la condició. Particularment, en les bombes de rotor humit, aquestos dos indicadors de fallada varíen sensiblement en funció del punt de càrrega hidràulica de la bomba. En l'ajuda de un mètode d'extracció de característiques basat en la "motor reference frame theory", es demostra que les mencionades freqüències es poden analitzar en temps real en un entorn industrial. A més a més, es presenten directrius per la monitorització en el núvol i es valida en l'ajuda de assajos en el laboratori. Addicionalment, es demostra que les fallades són també detectables quan s'analitza la corrent d'arrancada mitjançant ferramentes de descomposició temps-freqüència. Aquest fet no ha estat analitzat prèviament en cap tipus de literatura tècnica dins del camp de detecció de fallades en bombes. En conclusió, els resultats d'aquest treball demostren que els mètodes de diagnosi basats en la corrent poden detectar en èxit diversos tipus de fallades en bombes, el qual constitueix un punt d'interés per a l'indústria que utilitzen aquest tipus de actiu en els seus processos. / [EN] Pumps are the heart of many processes in industry and service sector. Electric motors are responsible for 69% of electric energy consumption in industry, with 22% of them being used for the operation of pumps. Pump faults can lead to process breakdowns and are thus related to high costs for the plant operator. Furthermore, faulty operation of pumps reduces the energy efficiency of the plant. In many cases, a time-based maintenance strategy is applied, which means that typical wear parts are replaced within defined time cycles, which comes with some drawbacks such as poor resource efficiency and high costs. Condition-based maintenance strategies - meaning that the replacement of parts is planned based on the condition of the pump - are often based on the evaluation of sensor signals like vibration or noise. However, the use of sensors also has some drawbacks, such as additional investment costs, frequent problems with the sensor mounting, and possible sensor faults. There is no widespread use of the current signal to make statements about the pump condition, although current sensors are installed in many applications anyway. As for motor fault diagnosis, different current-based techniques have demonstrated their function. Today, motor current signature analysis is used in industry, especially for the diagnosis of induction motors. In this thesis, the current-based diagnosis of typical pump-related faults in different applications is evaluated. In total, three different pump types are investigated: a wet-rotor pump, a dry-runner inline pump, and a submersible pump. The techniques used for motor fault detection are adapted for the diagnosis of pump-related faults. The results indicate that the faults clogging, impeller crack, and bearing wear, in particular, influence two frequencies in the current spectrum, which can be used as a basis for a condition-based maintenance strategy. Especially in wet-rotor pumps, these two fault indicators strongly vary depending on the hydraulic load point of the pump. With the help of a feature extraction method based on the adapted reference frame theory, this work demonstrates that the two frequencies can be analyzed in real time in a field environment. Furthermore, a concept for cloud monitoring is presented and validated with the help of a laboratory test. Additionally, it is demonstrated that the faults are visible if the starting current is evaluated in a time-frequency map, which has not been considered before in the literature on pump-related faults. In summary, the findings of this work indicate that current-based diagnosis methods can successfully detect typical faults in pumps, a fact that is of high interest for companies using these assets in their industrial processes. / Becker, V. (2022). Current-based Techniques for Condition Monitoring of Pumps [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/190630