Optimal Design of a Cam Mechanism with Translating Flat-Face Follower using Genetic Algorithm

The optimum design of a cam mechanism is a time consuming task, due to the numerous alternatives considerations. In the present work, the problem of design parameters optimization of a cam mechanism with translating flat - face follower is investigated from a multi - objective point of view. The design parameters, just like the cam base circle radius, the follower face width and the follower offset can be determined considering as the optimization criteria minimization of the cam size, of the input torque and of the contact stress. During the optimization procedure, a number of constraints regarding the pressure angle, the contact stress, etcare taken into account. The optimization approach, based on genetic algorithm, is applied to find the optimal solutions with respect to the a fore - mentioned objective function and to Ensure the kinematic requirements. Finally, the dynamic behavior of the designed cam mechanism is investigated considering the frictional forces

Detekcija otkaza kotrljajnih ležajeva primenom naprednih vremensko-frekvencijskih metoda analize signala vibracija

Rezime: Od samih početaka industrijske revolucije pojavila se potreba za što efikasnijom i pre svega jeftinijom proizvodnjom proizvoda koja će pri tom imati željeni visok nivo kvaliteta. U tu svrhu, kreiraju se sve brže i snažnije mašine i mehanizmi, koji postaju sve kompleksniji, a samim tim izloženiji višim nivoima opterećenja. Kao rezultat toga mašine su sve više izložene kompleksnijim tipovima oštećenja i/ili otkazima koji direktno utiču na njihovu pouzdanost, raspoloživost i bezbednost pri korišćenju. Takvu opremu srećemo u finansijski i tehnički posebno kritičnim oblastima kao što su: procesi obrade, transportni sistemi, električna i elektronska oprema, elektroenergetski sistemi, a u novije vreme su to sistemi za proizvodnju obnovljive energije. Rotacione mašine spadaju u klasu najčešće korišćenih tehničkih sistema, za koje se često zahteva kompletna i precizna dokumentacija o vibracionim karakteristikama, uključujući merenja neophodna kako bi se izvršila analiza vibracija vratila, kućišta i kotrljajnih ležajeva. Kotrljajni ležajevi, reduktori i rotori su ključne i neizostavne komponente rotacionih mašina. Samim tim, stanje ovih ključnih komponenata ujedno određuje i stanje same rotacione mašine. U disertaciji se proučava primena postprocesionih metoda izdvajanja spektra iz signala vibracija, kako bi se detektovala oštećenja kotrljajnih ležajeva. Kotrljajni ležajevi su osnovne komponente rotacionih mašina. Oštećenja kotrljajnih ležajeva su odgovorna za značajan deo otkaza mašina. Samim tim otkrivanje oštećenja kotrljajnih ležajeva je važno za poboljšanje pouzdanosti i performansi mehaničkih sistema. Iako su kotrljajni ležajevi detaljno proučavani tokom prethodnih decenija što je prikazano u dostupnoj literaturi, u ovoj disertaciji je predstavljena inovativna primena vremensko–frekvencijske metode za analizu, tzv. metode kompletne ansambalske empirijske dekompozicije na modove sa adaptivnim šumom (eng. Complete Ensemble Empirical Mode Decomposition with Adaptive Noise – CEEMDAN) i Zao–Atlas–Markove raspodele (ZAMD). Pomenutim metodama se prevazilaze poznata ograničenja metode razlaganja signala na funkcije (eng. Empirical Mode Decomposition – EMD), u pogledu mešanja modova i izdvajanja frekvencija. Glavni cilj disertacije je istraživanje sposobnosti ovih metoda za otkrivanje oštećenja u početnoj fazi. Za procenu metoda, koriste se kotrljajni ležajevi sa poznatim lokalizovanim oštećenjima, u cilju dobijanja skupa podataka sa eksperimentalnog postrojenja koje simulira rotacionu mašinu. Isto tako, upotrebljavaju se i podaci iz literature kao drugi test. Dobijeni rezultati potvrđuju sposobnost metode za otkrivanje degradacije kotrljajnih ležajeva.Abstract: Since the industrial revolution, a need for faster, better quality and especially cheaper to produce, products has emerged. So special tools, quick and powerful machines and mechanisms were created, and tend to become increasingly complex, thus subject to a corresponding complex damage and / or failures affecting the reliability, availability and safety of operation. Such equipment’s are found in particularly critical financial and technical fields such as machining processes, production, transport systems, electrical and electronic equipment and power systems (and, recently, renewable energy). Rotating machinery is one of the most common classes of machines, often requires complete and accurate documentation of vibration characteristics including measurements for shaft, housing and rolling bearings vibration analysis. Rolling bearings, gears and rotors are the common and key components in rotating machinery. The health condition of these key components represents that of the machine itself. The present dissertation introduces investigates the application of a post-processing method of extracting spectra from vibration signals in order to detect faults of rollingelement bearings. Rolling-element bearings are fundamental components of rotating machinery. Faults of rolling-elements bearings are responsible for a substantial proportion of machine failures and therefore fault detection is important for improving the mechanical system reliability and performance. Although rolling bearings have been investigated in detail in past studies, innovative applications of time-frequency analysis method, called complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and Zhao Atlas Marks Distribution (ZAMD), that overcomes known limitations concerning mode mixing and frequency separation of empirical mode decomposition are presented. The main aim of the presented dissertation is to investigate the ability of the methods to detect faults in early stage. To validate the methods, rollingelement bearings with known and localized faults are used in order to acquire datasets from an experimental rig that stimulates rotating machinery. Also datasets from literature are used as second trial. The results verify the ability of the method to detect degradations of rolling-element bearings. The present dissertation consists of six experimental studies and one industrial case study, where the first one was concerned with investigation and validation of the experimentalrig in relation to its dimensions and construction accuracy and the second one concerned the validation and selection of mounting pads in order to isolate the experimental-rig from external stimulations and the calculation of their mechanical properties. The four remaining experimental studies were concerned with investigation and validation of advanced signal processing methodologies for their ability to detect external stimulations and to detect faults in early stage in rolling- element bearings. At last an industrial case study was conducted in order to validate the method in real working environment

Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN

Drons col·laboratius

La robòtica col·laborativa és senzillament robots dissenyats per dur a terme treballs de col·laboració amb els humans. Els robots col·laboratius o cobots són cada cop més utilitzats a les indústries. La robòtica col·laborativa és un dels àmbits d'actualitat en aquests moments. Però també és un dels més interessants en més d'un sentit. Com es comuniquen dos drons autònoms que col·laboren per fer una tasca? Com són aquests missatges que s'envien? Que poden fer que no podrien fer sols? Aquestes són algunes de les preguntes que ens volem respondre en aquest projecte. En aquest treball es presenta un disseny i implementació de dos drons terrestres que es comuniquen per col·laborar entre ells per resoldre una tasca.Collaborative robotics is simply robots designed to perform collaborative work with humans. Collaborative robots or cobots are increasingly used in industries. Collaborative robotics is one of the current topics now. But it is also one of the most interesting in more ways than one. How do two autonomous drones that collaborate to perform a task communicate? How are these messages sent? What can they do that they could not do alone? These are some of the questions we want to answer in this project. This work presents a design and implementation of two ground drones that communicate to collaborate with each other to solve a task.La robótica colaborativa es sencillamente robots diseñados para llevar a cabo trabajos de colaboración con los humanos. Los robots colaborativos o cobots son cada vez más utilizados en las industrias. La robótica colaborativa es uno de los ámbitos de actualidad. Pero también es uno de los más interesantes en más de un sentido. ¿Cómo se comunican drones autónomos que colaboran para hacer una tarea? ¿Cómo son estos mensajes que es envían? ¿Qué pueden hacer que no lo podrían hacer solos? Estas son algunas de las preguntas que queremos responder con este proyecto. En este trabajo se presenta un diseño e implementación de dos drones terrestres que se comunican para colaborar entre ellos para resolver una tarea

Detekcija otkaza kotrljajnih ležajeva primenom naprednih vremensko-frekvencijskih metoda analize signala vibracija

Rezime: Od samih početaka industrijske revolucije pojavila se potreba za što efikasnijom i pre svega jeftinijom proizvodnjom proizvoda koja će pri tom imati željeni visok nivo kvaliteta. U tu svrhu, kreiraju se sve brže i snažnije mašine i mehanizmi, koji postaju sve kompleksniji, a samim tim izloženiji višim nivoima opterećenja. Kao rezultat toga mašine su sve više izložene kompleksnijim tipovima oštećenja i/ili otkazima koji direktno utiču na njihovu pouzdanost, raspoloživost i bezbednost pri korišćenju. Takvu opremu srećemo u finansijski i tehnički posebno kritičnim oblastima kao što su: procesi obrade, transportni sistemi, električna i elektronska oprema, elektroenergetski sistemi, a u novije vreme su to sistemi za proizvodnju obnovljive energije. Rotacione mašine spadaju u klasu najčešće korišćenih tehničkih sistema, za koje se često zahteva kompletna i precizna dokumentacija o vibracionim karakteristikama, uključujući merenja neophodna kako bi se izvršila analiza vibracija vratila, kućišta i kotrljajnih ležajeva. Kotrljajni ležajevi, reduktori i rotori su ključne i neizostavne komponente rotacionih mašina. Samim tim, stanje ovih ključnih komponenata ujedno određuje i stanje same rotacione mašine. U disertaciji se proučava primena postprocesionih metoda izdvajanja spektra iz signala vibracija, kako bi se detektovala oštećenja kotrljajnih ležajeva. Kotrljajni ležajevi su osnovne komponente rotacionih mašina. Oštećenja kotrljajnih ležajeva su odgovorna za značajan deo otkaza mašina. Samim tim otkrivanje oštećenja kotrljajnih ležajeva je važno za poboljšanje pouzdanosti i performansi mehaničkih sistema. Iako su kotrljajni ležajevi detaljno proučavani tokom prethodnih decenija što je prikazano u dostupnoj literaturi, u ovoj disertaciji je predstavljena inovativna primena vremensko–frekvencijske metode za analizu, tzv. metode kompletne ansambalske empirijske dekompozicije na modove sa adaptivnim šumom (eng. Complete Ensemble Empirical Mode Decomposition with Adaptive Noise – CEEMDAN) i Zao–Atlas–Markove raspodele (ZAMD). Pomenutim metodama se prevazilaze poznata ograničenja metode razlaganja signala na funkcije (eng. Empirical Mode Decomposition – EMD), u pogledu mešanja modova i izdvajanja frekvencija. Glavni cilj disertacije je istraživanje sposobnosti ovih metoda za otkrivanje oštećenja u početnoj fazi. Za procenu metoda, koriste se kotrljajni ležajevi sa poznatim lokalizovanim oštećenjima, u cilju dobijanja skupa podataka sa eksperimentalnog postrojenja koje simulira rotacionu mašinu. Isto tako, upotrebljavaju se i podaci iz literature kao drugi test. Dobijeni rezultati potvrđuju sposobnost metode za otkrivanje degradacije kotrljajnih ležajeva.Abstract: Since the industrial revolution, a need for faster, better quality and especially cheaper to produce, products has emerged. So special tools, quick and powerful machines and mechanisms were created, and tend to become increasingly complex, thus subject to a corresponding complex damage and / or failures affecting the reliability, availability and safety of operation. Such equipment’s are found in particularly critical financial and technical fields such as machining processes, production, transport systems, electrical and electronic equipment and power systems (and, recently, renewable energy). Rotating machinery is one of the most common classes of machines, often requires complete and accurate documentation of vibration characteristics including measurements for shaft, housing and rolling bearings vibration analysis. Rolling bearings, gears and rotors are the common and key components in rotating machinery. The health condition of these key components represents that of the machine itself. The present dissertation introduces investigates the application of a post-processing method of extracting spectra from vibration signals in order to detect faults of rollingelement bearings. Rolling-element bearings are fundamental components of rotating machinery. Faults of rolling-elements bearings are responsible for a substantial proportion of machine failures and therefore fault detection is important for improving the mechanical system reliability and performance. Although rolling bearings have been investigated in detail in past studies, innovative applications of time-frequency analysis method, called complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and Zhao Atlas Marks Distribution (ZAMD), that overcomes known limitations concerning mode mixing and frequency separation of empirical mode decomposition are presented. The main aim of the presented dissertation is to investigate the ability of the methods to detect faults in early stage. To validate the methods, rollingelement bearings with known and localized faults are used in order to acquire datasets from an experimental rig that stimulates rotating machinery. Also datasets from literature are used as second trial. The results verify the ability of the method to detect degradations of rolling-element bearings. The present dissertation consists of six experimental studies and one industrial case study, where the first one was concerned with investigation and validation of the experimentalrig in relation to its dimensions and construction accuracy and the second one concerned the validation and selection of mounting pads in order to isolate the experimental-rig from external stimulations and the calculation of their mechanical properties. The four remaining experimental studies were concerned with investigation and validation of advanced signal processing methodologies for their ability to detect external stimulations and to detect faults in early stage in rolling- element bearings. At last an industrial case study was conducted in order to validate the method in real working environment

ATLAS muon precision chamber construction at the University of Thessaloniki

ATLAS is one of the two general purpose experiments being built for the LHC at CERN. Its Muon Spectrometer consists of high precision chambers made of drift tubes (MDTs = Monitored Drift Tubes). The properties and the performance of the chambers is described. Highlights of the construction and the quality control of the first chamber of type BIS to be used in ATLAS are presented. 7 Refs