Condition monitoring of pipelines

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Novel efficient technologies in Europe for axle bearing condition monitoring – the MAXBE project

Axle bearing damage with possible catastrophic failures can cause severe disruptions or even dangerous derailments, potentially causing loss of human life and leading to significant costs for railway infrastructure managers and rolling stock operators. Consequently the axle bearing damage process has safety and economic implications on the exploitation of railways systems. Therefore it has been the object of intense attention by railway authorities as proved by the selection of this topic by the European Commission in calls for research proposals. The MAXBE Project (http://www.maxbeproject.eu/), an EU-funded project, appears in this context and its main goal is to develop and to demonstrate innovative and efficient technologies which can be used for the onboard and wayside condition monitoring of axle bearings. The MAXBE (interoperable monitoring, diagnosis and maintenance strategies for axle bearings) project focuses on detecting axle bearing failure modes at an early stage by combining new and existing monitoring techniques and on characterizing the axle bearing degradation process. The consortium for the MAXBE project comprises 18 partners from 8 member states, representing operators, railway administrations, axle bearing manufactures, key players in the railway community and experts in the field of monitoring, maintenance and rolling stock. The University of Porto is coordinating this research project that kicked-off in November 2012 and it is completed on October 2015. Both on-board and wayside systems are explored in the project since there is a need for defining the requirement for the onboard equipment and the range of working temperatures of the axle bearing for the wayside systems. The developed monitoring systems consider strain gauges, high frequency accelerometers, temperature sensors and acoustic emission. To get a robust technology to support the decision making of the responsible stakeholders synchronized measurements from onboard and wayside monitoring systems are integrated into a platform. Also extensive laboratory tests were performed to correlate the in situ measurements to the status of the axle bearing life. With the MAXBE project concept it will be possible: to contribute to detect at an early stage axle bearing failures; to create conditions for the operational and technical integration of axle bearing monitoring and maintenance in different European railway networks; to contribute to the standardization of the requirements for the axle bearing monitoring, diagnosis and maintenance. Demonstration of the developed condition monitoring systems was performed in Portugal in the Northern Railway Line with freight and passenger traffic with a maximum speed of 220 km/h, in Belgium in a tram line and in the UK. Still within the project, a tool for optimal maintenance scheduling and a smart diagnostic tool were developed. This paper presents a synthesis of the most relevant results attained in the project. The successful of the project and the developed solutions have positive impact on the reliability, availability, maintainability and safety of rolling stock and infrastructure with main focus on the axle bearing health.

Design and implementation of a vibrational condition monitoring system

Industrial companies, particularly those with induction motors and gearboxes as integral components of their systems, are utilizing Condition Monitoring (CM) systems more frequently in order to discover the need for maintenance in advance, as traditional maintenance only performs tasks when a failure has been identified. Utilizing a CM system is essential to boost productivity and minimize long-term failures that result in financial loss. The more exact and practical the CM system, the better the data analysis, which adds to a more precise maintenance forecast. This thesis project is a cooperation with PEI Vibration Monitoring s.r.l. to design and construct a low-cost vibrational condition monitoring system to check the health of induction motors and gearboxes automatically. Moreover, according to the company's request, such a system should have specs comparable to NI 9234, one of the company's standard Data Acquisition (DAQ) boards, but at a significantly cheaper price. Additionally, PEI VM Company has supplied all hardware and electronic components. The suggested CM system is capable of highprecision autonomous monitoring of induction motors and gearboxes, and it consists of a Raspberry Pi 3B and MCC 172 DAQ board.

Elintarviketehtaan tuotantolinjan kunnonvalvonnan kehittäminen

Tutkimuksen tavoitteena oli kunnonvalvontajärjestelmän kehittäminen nykyaikaiselle elintarviketeollisuuden tuotantolinjalle. Työssä etsittiin olemassa olevia kunnonvalvontamenetelmiä ja -sovelluksia erityisesti jäätelötuotantolaitteiden tarpeisiin. Kirjallisuudesta löydettiin sovelluksia lähinnä yksittäisille komponenteille ja kone-elimille. Tutkimuksen kohteena oleva tuotantolinja käytiin läpi toimintojen ja komponenttien osalta. Tehtaan laitekantaa ja valmiutta kunnonvalvonnan käyttöönotolle käsiteltiin yleisellä tasolla. Kunnonvalvontajärjestelmää kehitettäessä käytettiin hyväksi kirjallisuudesta löytyneitä menetelmiä, joista soveltuvimpia käytettiin kunnonvalvontametodien kartoittamiseen. Kunnonvalvontametodit muodostettiin toiminnanohjausjärjestelmästä ja linjan käyttöönotosta saatujen tietojen avulla. Tietoja käytettiin vika-vaikutusanalyysissä, joka oli pohjana komponentti- ja menetelmäkohtaisessa analyysissa. Kriittisiä ja tuotannon tehokkuuteen vaikuttavia koneenosia ja kokonaisuuksia tarkasteltiin kunnonvalvontamenetelmien soveltuvuuden avulla. Tutkimuksen edetessä kehitettiin kokonaisvaltaiset toiminnanohjausjärjestelmän avulla toimivat eritasoiset kunnonvalvontahypoteesit, joiden avulla linjan yksittäisten komponenttien kuntoa voidaan valvoa. Lisäksi tutkimuksessa kehitettiin uusia kunnonvalvontasovelluksia, joita on mahdollista käyttää myös tehtaan muilla linjoilla. Kunnonvalvontahypoteeseja käytettiin kokonaisen kunnonvalvontajärjestelmän luomiseen. Tehtaalla on mahdollisuus valita käyttöönotettavan kunnonvalvonnan taso hypoteesien sekä kunnossapitostrategian avulla.

The importance of control monitoring systems in wind parks maintenance

The objective of every wind energy producer is to reduce operational costs associated to the production as a way to increase profits. One other issue that must be looked carefully is the equipment maintenance. Increase the availability of wind turbines by reducing the downtime associated to failures is a good strategy to achieve the main goal of increase profits. As a way to help in the definition of the best maintenance strategies, condition monitoring systems (CMS) have an important role to play. Informatics tools to make the condition monitoring of the wind turbines were developed and are now being installed as a way to help producers reducing the operational costs. There are a lot of developed systems to do the monitoring of a wind turbine or the whole wind park, in this paper will be made an overview of the most important systems.

Emotional modulation of memory encoding and performance monitoring

Performance monitoring, ERN, CRN, Pe, Memory, Llist learning, Emotion, IAPS, N2, Reinforcement Learning Hypothesis, Conflict Monitoring Hypothesis

Monitoring of centrifugal pump operation by a frequency converter

Centrifugal pumps are widely used in industrial and municipal applications, and they are an important end-use application of electric energy. However, in many cases centrifugal pumps operate with a significantly lower energy efficiency than they actually could, which typically has an increasing effect on the pump energy consumption and the resulting energy costs. Typical reasons for this are the incorrect dimensioning of the pumping system components and inefficiency of the applied pump control method. Besides the increase in energy costs, an inefficient operation may increase the risk of a pump failure and thereby the maintenance costs. In the worst case, a pump failure may lead to a process shutdown accruing additional costs. Nowadays, centrifugal pumps are often controlled by adjusting their rotational speed, which affects the resulting flow rate and output pressure of the pumped fluid. Typically, the speed control is realised with a frequency converter that allows the control of the rotational speed of an induction motor. Since a frequency converter can estimate the motor rotational speed and shaft torque without external measurement sensors on the motor shaft, it also allows the development and use of sensorless methods for the estimation of the pump operation. Still today, the monitoring of pump operation is based on additional measurements and visual check-ups, which may not be applicable to determine the energy efficiency of the pump operation. This doctoral thesis concentrates on the methods that allow the use of a frequency converter as a monitoring and analysis device for a centrifugal pump. Firstly, the determination of energy-efficiency- and reliability-based limits for the recommendable operating region of a variable-speed-driven centrifugal pump is discussed with a case study for the laboratory pumping system. Then, three model-based estimation methods for the pump operating location are studied, and their accuracy is determined by laboratory tests. In addition, a novel method to detect the occurrence of cavitation or flow recirculation in a centrifugal pump by a frequency converter is introduced. Its sensitivity compared with known cavitation detection methods is evaluated, and its applicability is verified by laboratory measurements for three different pumps and by using two different frequency converters. The main focus of this thesis is on the radial flow end-suction centrifugal pumps, but the studied methods can also be feasible with mixed and axial flow centrifugal pumps, if allowed by their characteristics.

Variable speed drive in fan system monitoring

Fan systems are responsible for approximately 10% of the electricity consumption in industrial and municipal sectors, and it has been found that there is energy-saving potential in these systems. To this end, variable speed drives (VSDs) are used to enhance the efficiency of fan systems. Usually, fan system operation is optimized based on measurements of the system, but there are seldom readily installed meters in the system that can be used for the purpose. Thus, sensorless methods are needed for the optimization of fan system operation. In this thesis, methods for the fan operating point estimation with a variable speed drive are studied and discussed. These methods can be used for the energy efficient control of the fan system without additional measurements. The operation of these methods is validated by laboratory measurements and data from an industrial fan system. In addition to their energy consumption, condition monitoring of fan systems is a key issue as fans are an integral part of various production processes. Fan system condition monitoring is usually carried out with vibration measurements, which again increase the system complexity. However, variable speed drives can already be used for pumping system condition monitoring. Therefore, it would add to the usability of a variablespeed- driven fan system if the variable speed drive could be used as a condition monitoring device. In this thesis, sensorless detection methods for three lifetime-reducing phenomena are suggested: these are detection of the fan contamination build-up, the correct rotational direction, and the fan surge. The methods use the variable speed drive monitoring and control options for the detection along with simple signal processing methods, such as power spectrum density estimates. The methods have been validated by laboratory measurements. The key finding of this doctoral thesis is that a variable speed drive can be used on its own as a monitoring and control device for the fan system energy efficiency, and it can also be used in the detection of certain lifetime-reducing phenomena.

A synthetic control chart for monitoring the process mean and variance

Purpose - The aim of this paper is to present a synthetic chart based on the non-central chi-square statistic that is operationally simpler and more effective than the joint X̄ and R chart in detecting assignable cause(s). This chart will assist in identifying which (mean or variance) changed due to the occurrence of the assignable causes. Design/methodology/approach - The approach used is based on the non-central chi-square statistic and the steady-state average run length (ARL) of the developed chart is evaluated using a Markov chain model. Findings - The proposed chart always detects process disturbances faster than the joint X̄ and R charts. The developed chart can monitor the process instead of looking at two charts separately. Originality/value - The most important advantage of using the proposed chart is that practitioners can monitor the process by looking at only one chart instead of looking at two charts separately. © Emerald Group Publishing Limted.

Adesão ao tratamento da malária: um estudo em comunidades do entorno da Usina Hidrelétrica de Tucuruí - Pará

Malária, doença infecciosa causada pelo protozoário Plasmodium, transmitida ao homem pela picada de mosquito fêmea do gênero Anopheles, atualmente põe em risco 40% da população mundial. No Brasil, ocorre sobretudo na Região Amazônica, onde estão concentrados 99,7% dos casos. Nas comunidades localizadas no entorno do lago de Tucuruí, a ocorrência de malária é elevada e os moradores não contam com serviços eficientes que proporcionem profilaxia e terapia adequados. Esta pesquisa teve a finalidade de analisar a ocorrência de comportamentos de adesão ao tratamento medicamentoso e de prevenção da malária em indivíduos residentes em comunidades do entorno da Usina Hidrelétrica de Tucuruí, Estado do Pará, por meio da comparação de três condições de intervenção: Rotina (n=10), Monitoramento (n=9) e Informação com monitoramento (n=10). Para avaliar quantitativamente os efeitos da intervenção, os comportamentos adotados nas três condições foram comparados por testes não-paramétricos (Qui-Quadrado e teste Binomial). A adesão ao tratamento nas condições Rotina e Monitoramento foi inexpressiva, enquanto, na condição Informação com monitoramento após a intervenção, 80% dos participantes apresentaram relatos de adesão ao tratamento significativamente superior, evidenciando eficácia da intervenção. Quanto ao conhecimento da malária na condição Informação com monitoramento, a intervenção promoveu aumento no nível de conhecimento dos participantes sobre a malária. A análise da mudança no repertório comportamental foi realizada em treze itens. Foram alcançados resultados mais expressivos na condição Informação com monitoramento; em nove itens foi observada mudança significativa de atitude dos participantes. A comparação entre as condições Monitoramento e Informação com monitoramento apresentou diferença significativa em oito itens: usar mosquiteiro, notificar o agente de saúde, manter cortadas ou podadas as árvores, não tomar banho no rio em horários de risco, usar roupa adequada para adentrar à mata, usar roupa adequada para pescar, não ficar no relento e usar repelentes como andiroba ou similares. Em síntese, conclui-se que a intervenção Informação com monitoramento foi eficaz para melhorar a adesão ao tratamento da malária e o nível de conhecimento sobre a doença.

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.

Gear dynamics monitoring using discrete wavelet transformation and multi-layer perceptron neural networks

This paper presents a multi-stage algorithm for the dynamic condition monitoring of a gear. The algorithm provides information referred to the gear status (fault or normal condition) and estimates the mesh stiffness per shaft revolution in case that any abnormality is detected. In the first stage, the analysis of coefficients generated through discrete wavelet transformation (DWT) is proposed as a fault detection and localization tool. The second stage consists in establishing the mesh stiffness reduction associated with local failures by applying a supervised learning mode and coupled with analytical models. To do this, a multi-layer perceptron neural network has been configured using as input features statistical parameters sensitive to torsional stiffness decrease and derived from wavelet transforms of the response signal. The proposed method is applied to the gear condition monitoring and results show that it can update the mesh dynamic properties of the gear on line.

Estágio na empresa SPECMAN para a prática de técnicas de controlo da condição

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Análise por ultra-sons no controlo de condição

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Diagnóstico de avarias em máquinas rotativas utilizando a análise de órbitas

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica Perfil Manutenção e Produção