Title Nadzor oštrice reznog alata korištenjem signala upravljačkog sustava Title (english) Monitoring of cutting tool wear by using signals of the control system Author Tihomir Mulc Mentor Toma Udiljak (mentor)Committee member Branko Novaković (predsjednik povjerenstva)Committee member Toma Udiljak (član povjerenstva)Committee member Nikola Šakić (član povjerenstva)Committee member Janez Kopač (član povjerenstva) Committee member Davor Zorc (član povjerenstva)Granter University of Zagreb Defense date and country 2012-01-27, Croatia Scientific / art field, TECHNICAL SCIENCES Universal decimal classificationUDC ) 621 - Mechanical engineering. Nuclear technology. Machinery Abstract Za blago prizemljenje aviona potrebno je da vješt i iskusan pilot uskladi upravljačke aktivnosti sa stanjem i položajem aviona, uzimajući u obzir vanjske poremećaje (vjetar, kiša snijeg, signalizacija..). Pogreška u bilo kojem trenutku procesa upravljanja, ili značajnije zanemarivanje vanjskih utjecaja, može imati za posljedicu grubo prizemljenje ili u najgorem slučaju pad. Slična se analogija može primijeniti i na proces nadgledanja stanja alata i stroja kao temelja fleksibilne autonomne proizvodnje. Proces obrade je izuzetno dinamičan, kompleksan i ovisan o nizu utjecaja. \Ne može se promatrati izdvojeno, već zahtijeva holistički pristup u kojem se menusobno prožimaju karakteristike stroja, procesa, alata, obratka i okoline. Djelomično promatranje sustava i nemogućnost prenosivosti pojedinih rješenja, nadgledanje procesa obrade izdvaja kao ograničavajućih faktora u globalnoj primjenjivosti autonomnih sustava. Prilagonavanje okolini i uvjetima procesa, jednostavnost i brzina učenja, ključne su komponente uspješnosti budućih sustava nadzora i bitna pretpostavka prenosivosti metoda nadzora. Shodno tome ovaj rad je rezultat nastojanja da se obuhvati cjeloviti prikaz procesa nadgledanja alata i predloži jedno od mogućih rješenja. U prvom dijelu rada opisana je struktura obradnih strojeva, a potom i procesa obrade s težištem na glodanje. Analizirani su oblici i mehanizmi trošenja te metode prihvata i obrade signala. Predložen je skup značajki te postupak izbora dominantnih značajki u odnosu na promatranu pojavu. Analizirani su utjecaji trošenja alata na pojedine značajke. Provedena je analiza postojećih sustava nadzora, te je predložen sustav temeljen na modularno orijentiranoj strukturi koja dozvoljava razvoj softverskih modula za različita područja rada. Postavljene su osnove procjene parametara posmičnih osi kao sredstva izdvajanja mehaničkog dijela šuma iz digitalnih signala pogonskih sustava obradnog stroja s ciljem izbjegavanja potreba za dodatnim senzorima i hardverskim sklopovima. Opisan je postupak odrenivanja funkcija obradivosti kao mogućeg sredstva nadopune mjerenih podataka u svrhu skraćenja učenja neuronskih mreža. Korištena je neparametarska spektralna analiza signala kod detektiranja krzanja alata. Opisana je struktura modularne neuronske mreže kao temelja budućih sustava strukturiranih od lokalnih eksperata osposobljenih za pojedina područja djelovanja. U drugom dijelu rada, kroz provedeno eksperimentalno istraživanje, verificirane su predložene metode. Analiziran je odabir značajki trošenja kod različitih uvjeta odvijanja eksperimenta. Testiran je utjecaj kombinacija različitih značajki na kvalitetu nadzora. Analiziran je utjecaj promjene tvrdoće i dubine obranivanog materijala, na ponašanje predloženog sustava nadzora. Istražen je potencijal sustava nadzora alata integriranog u upravljački sustav stroja. Testirana je neparametarska metoda procjene spektra snage kod krzanja alata za proces glodanja.
Abstract (english) For a gentle aircraft landing, it takes a skilled and experience pilot to harmonize the control activities with the state and position of the aircraft, while considering external disturbances (wind, rain, snow, signalization, etc.). An error at any time in the control process or significant disregard of the external factors can result in a rough landing or, in the worst case, a crash. A similar analogy can be applied to the process of monitoring the state of tools and machinery as the foundation of flexible autonomous production. The processing procedure is exceptionally dynamic and complex, and is reliant on a series of variables. These cannot be considered separately, but rather demands a holistic approach in which the characteristics of the machine, processes, tools, treatment and environment are intertwined. A partial examination of the system and the inability to transfer individual solutions makes the monitoring of processing procedure a limiting factor in the global applicability of autonomous systems. Adaptation to the environmental and processing conditions, and simple and fast learning are the key components for success in future supervision systems, and an important assumption in the transferability of supervision methods. As such, this paper is the result of an attempt to give a comprehensive overview of the tool monitoring process, and to propose a possible solution. The first part of the dissertation describes the structure of processing machines, followed by a description of the processing procedure, focusing on milling. The forms and mechanisms of wear and the methods of receiving the processing signal are analysed. A group of characteristics and the procedure for selecting the dominant characteristics in relation to the observed state are analysed. The influences of tool wear on individual characteristics are also analysed. An analysis of existing supervision systems is given, and a system based on a modularly oriented structure is proposed to allow for the development of software modules for various areas of work. A basic assessment is given of parameters of variable tangential axes as the means for separating out the mechanical part of the noise from digital signals of plant machine processing systems, in order to avoid the need for additional sensors and hardware. The procedure for determining the function of processability is described, as a possible means of supplementing measured data in detecting tool fraying. The structure of the modular neuron network, built by local experts specialized in individual areas of expertise, is described as the foundation of future systems. In the second part of the dissertation, the proposed methods are verified through experimental research. The selection of wear properties is analysed under different experimental conditions. The influence of a combination of various properties on monitoring quality is tested. The influence of changes in hardness and depth of the processed material, and the behaviour of the proposed monitoring system are analysed. The potential of the tool monitoring system, integrated into the machine management system, is investigated. The non-parametric method of assessing the strength spectrum in tool fraying for the milling process is tested.
Keywords
obradni sustavi
proces obrade odvajanjem čestica
sustav nadzora oštrice reznog alata
procjena parametara
planiranje pokusa
modularnost
umjetna inteligencija
Keywords (english)
processing systems
particle separation processing
cutting tool blade supervision system
parameter assessment
experimental planning
modularity
artificial intelligence
Language croatian URN:NBN urn:nbn:hr:235:023018 Study programme Title: Mechanical Engineering and Naval Architecture Type of resource Text File origin Born digital Access conditions Closed access Terms of use Created on 2020-05-11 09:22:07
