Control hardware and Condition Monitoring System for Intersector Weld/Cut Robot

Työ sisältää ohjaislaitteiston vertailun ja valinnan rinnakkaisrakenteista robottia varten sekä kunnonvalvontajärjestelmän periaatteiden laadinnan kyseistä robottia varten. Ohjauslaitteisto sisältää teollisuustietokoneen sekä kenttäväylän. Sekä tietokoneesta että väylästä on teoriaosuus ja yksityiskohtaisempi valintaosuus. Teoriaosuudessa selitetään tarkemmin laitteiden toimintaperiaatteista. Valintaosuudessa kerrotaanmiksi jokin tietty laite on valittu käytettäväksi robotin ohjauksessa. Kunnonvalvontateoria ja rinnakkaisrakenteisen robotin kunnonvalvonnan keinot ovat työn toinen osa. Teoriaosa sisältää yleisluonteisen selvityksen vikaantumisesta ja valvonnasta. Erikoisrobotin kunnonvalvonnan keinot esitetään työssä tietyssä järjestyksessä. Ensin esitetään mahdolliset vikatilanteet. Toisessa kohdassa havainnollistetaan vikojen havaitseminen.

Design of a Condition Monitoring System for a Glass Wool Production Line

Työn tarkoituksena oli suunnitella kunnonvalvontajärjestelmä kahdelle lasivillan tuotantolinjalle. Suunnitteluprosessin lisäksi työssä on esitelty erilaisia kunnonvalvontamenetelmiä. Työn alussa on kerrottu erilaisista kunnonvalvontamenetelmistä, joilla voidaan seurata erilaisten laitteiden ja koneiden toimintakuntoa.Erityisesti työssä on tarkasteltu teollisuudessa yleistyviä kunnonvalvonnan värähtelymittauksia. Työssä suunniteltu kunnonvalvontajärjestelmä perustuu viiteen eri menetelmään, jotka ovat värähtelymittaus, lämpötilanmittaus lämpökameralla, lämpötilanmittaus kannettavalla mittarilla, kuuntelu elektronisella stetoskoopilla ja pyörivien osien kunnontarkkailu stroboskoopilla. Kunnonvalvontajärjestelmän suunnittelu on tehty useassa eri vaiheessa. Ensin työssä on kartoitettu tuotannon kannalta tärkeimmät laitteet ja niiden mahdolliset vikaantumistavat. Seuraavaksi on valittu sopivat kunnonvalvontamenetelmät ja tehty mittaussuunnitelma, jossa on esitetty eri laitteille suoritettavat mittaukset ja mittausten aikavälit.Lopuksi työssä on esitelty muutama esimerkkitapaus kunnonvalvontamenetelmien käytöstä sekä kerrottu mahdollisista tulevaisuuden kehitysmahdollisuuksista.

Applicability of Power-Line Communications to Data Transfer of On-line Condition Monitoring of Electrical Drives

The research of power-line communications has been concentrated on home automation, broadband indoor communications and broadband data transfer in a low voltage distribution network between home andtransformer station. There has not been carried out much research work that is focused on the high frequency characteristics of industrial low voltage distribution networks. The industrial low voltage distribution network may be utilised as a communication channel to data transfer required by the on-line condition monitoring of electric motors. The advantage of using power-line data transfer is that it does not require the installing of new cables. In the first part of this work, the characteristics of industrial low voltage distribution network components and the pilot distribution network are measured and modelled with respect topower-line communications frequencies up to 30 MHz. The distributed inductances, capacitances and attenuation of MCMK type low voltage power cables are measured in the frequency band 100 kHz - 30 MHz and an attenuation formula for the cables is formed based on the measurements. The input impedances of electric motors (15-250 kW) are measured using several signal couplings and measurement based input impedance model for electric motor with a slotted stator is formed. The model is designed for the frequency band 10 kHz - 30 MHz. Next, the effect of DC (direct current) voltage link inverter on power line data transfer is briefly analysed. Finally, a pilot distribution network is formed and signal attenuation in communication channels in the pilot environment is measured. The results are compared with the simulations that are carried out utilising the developed models and measured parameters for cables and motors. In the second part of this work, a narrowband power-line data transfer system is developed for the data transfer ofon-line condition monitoring of electric motors. It is developed using standardintegrated circuits. The system is tested in the pilot environment and the applicability of the system for the data transfer required by the on-line condition monitoring of electric motors is analysed.

Venttiilien kunnossapidon optimointi

Tässä työssä tarkastellaan venttiilien kunnossapitoa ja erityisesti niiden kunnonvalvontaa. Työssä on kerrottu perusteita venttiileiden kunnonvalvonnan suorittamiseksi, venttiili- ja toimilaitevikojen perussyistä ja niiden havaitsemisesta. Työn pääpaino on kuitenkin kunnonvalvontamenetelmissä ja niiden käytössä. Mittauksia venttiilivuodon havaitsemiseksi suoritettiin akustisen emission, ultraäänen ja lämpötilan pistemittauksen avulla. Venttiilien yleistä kuntoa määritettiin värähtelyn, venymäliuskojen ja laitoksella jo toimivan moottoritoimilaitteen virtamittauksen avulla. Työssä on annettu suuntaviivat tulosten tulkitsemiselle, mutta yksityiskohtainen ja tarkempi tulosten tulkinnan määrittäminen jätetään laitoksen henkilökunnasta sille henkilölle joka mittauksia tulee tekemään tai jonka työnkuvaan muuten kuuluu kyseisten tulosten tulkitseminen.

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.

Remote Condition Monitoring and Asset Management in Offshore Power Systems

Condition monitoring systems for physical assets are constantly becoming more and more common in the industrial sector. At the same time an increasing portion of asset monitoring systems are being remotely supported. As global competitors are actively developing solutions for condition monitoring and condition-based maintenance, which it enables, Wärtsilä too feels the pressure to provide customers with more sophisticated condition-based maintenance solutions. The main aim of this thesis study is to consider Wärtsilä remote condition monitoring solutions and how they relate to similar solutions from other suppliers and end customers’ needs, in the context of offshore assets. A theoretical study is also included in the thesis, where the concepts of condition monitoring, condition-based maintenance, maintenance management and physical asset management are introduced.

Performance impact of the application of castor oil biodiesel in diesel engines

The use of renewable fuels, such as the biodiesel, can ease the demand of fossil fuel for the power generation and transportation fields in rural area. In this work, the performance impact of the application of castor oil biodiesel is evaluated with an automotive and a stationary diesel engine. The application of B20 and B10 biodiesel blends and pre-heated net biodiesel is considered. The viability of the employment of B10 and B20 blends to mobility and power generation was observed from dynamometric bench tests, where this blends performed similar to fossil diesel. With the pre-heated net biodiesel, however, a brake torque loss and a specific consumption increase were observed with relation to diesel fuel.

Techno-Economic Feasibility of Novel On-Line Condition Monitoring Methods in Low Voltage Distribution Networks

The focus in this thesis is to study both technical and economical possibilities of novel on-line condition monitoring techniques in underground low voltage distribution cable networks. This thesis consists of literature study about fault progression mechanisms in modern low voltage cables, laboratory measurements to determine the base and restrictions of novel on-line condition monitoring methods, and economic evaluation, based on fault statistics and information gathered from Finnish distribution system operators. This thesis is closely related to master’s thesis “Channel Estimation and On-line Diagnosis of LV Distribution Cabling”, which focuses more on the actual condition monitoring methods and signal theory behind them.

Fracture modes and acoustic emission characteristics of hydrogen-assisted cracking in high-strength low-alloy steel weldment

The aim of the present paper is to study the relationship between the fracture modes in hydrogen-assisted cracking (HAC) in microalloied steel and the emission of acoustic signals during the fracturing process. For this reason, a flux-cored arc weld (FCAW) was used in a high-strength low-alloy steel. The consumable used were the commercially available AWS E120T5-K4 and had a diameter of 1.6 mm. Two different shielding gases were used (CO2 and CO2+5% H2) to obtain complete phenomenon characterization. The implant test was applied with three levels of restriction stresses. An acoustic emission measurement system (AEMS) was coupled to the implant test apparatus. The output signal from the acoustic emission sensor was passed through an electronic amplifier and processed by a root mean square (RMS) voltage converter. Fracture surfaces were examined by scanning electron microscopy (SEM) and image analysis. Fracture modes were related with the intensity, the energy and the number of the peaks of the acoustic emission signal. The shielding gas CO2+5% H2 proved to be very useful in the experiments. Basically, three different fracture modes were identified in terms of fracture appearance: microvoid coalescence (MVC), intergranular (IG) and quasi-cleavage (QC). The results show that each mode of fracture presents a characteristic acoustic signal.

Automating condition monitoring of vegetation on railway trackbeds and embankments

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

Detection of cracks in scratching tests in ceramic materials through acoustic emission

The mechanisms of material removal and the interactions among scratches performed in ceramic materials were investigated using acoustic emission signals, and scanning electron microscopy, in scratching experiments. Several testing conditions were used to produce different types of removing mechanism on a glass as well as on a polycrystalline alumina sample composed by heterogeneous grain size. It is known that the material removing process on a polycrystalline ceramic involves intergranular microfracture and grain dislodgement, unlike the chipping produced by the extension of lateral cracks in non-granular materials, such as glass. Distinct settings for velocities, loads, and two types of diamond indenter were tested. The material removal was carried out by three different methods of scratching: single passes, repeated overlapping passes, and parallel scratches. As a general result, there was a clear relationship between the acoustic emission signals and the damage intensity occurred in the material removal. More specifically, there were differences in the acoustic emission signal levels in the scratches made on the alumina and on the glass owing to the material removal mechanisms associated with the structure of these materials. A gradual increase in the acoustic emission levels was observed when the number of repeated passes was increased as a result of the damage accumulation process followed by severe material removal. It was also noticed that the acoustic emission signals were capable of reflecting the interactions between two parallel scratches.