Functional restructuring of CAD models for FEA purposes

International audienceDigital Mock-ups (DMUs) are widespread and stand as reference model for product description. However, DMUs produced by industrial CAD systems essentially contain geometric models and their exploitation often requires user's input data to derive finite element models (FEMs). Here, analysis and reasoning approaches are developed to automatically enrich DMUs with functional and kinematic properties. Indeed, geometric interfaces between components form a key starting point to analyse their behaviours under reference states. This is a first stage in a reasoning process to progressively identify mechanical, kinematic as well as functional properties of the components. Inferred semantics adds up to the pure geometric representation provided by a DMU and produce also geometrically structured components and assemblies. Functional information connected to a structured geometric model of a component significantly improves the preparation of FEMs and increases its robustness because idealizations can take place using components' functions and components' structure helps defining sub-domains of FEMs

The use of mechanical redundancy for fault detection in non-stationary machinery

The classical approach to machinery fault detection is one where a machinery’s condition is constantly compared to an established baseline with deviations indicating the occurrence of a fault. With the absence of a well-established baseline, fault detection for variable duty machinery requires the use of complex machine learning and signal processing tools. These tools require extensive data collection and expert knowledge which limits their use for industrial applications. The thesis at hand investigates the problem of fault detection for a specific class of variable duty machinery; parallel machines with simultaneously loaded subsystems. As an industrial case study, the parallel drive stations of a novel material haulage system have been instrumented to confirm the mechanical response similarity between simultaneously loaded machines. Using a table-top fault simulator, a preliminary statistical algorithm was then developed for fault detection in bearings under non-stationary operation. Unlike other state of the art fault detection techniques used in monitoring variable duty machinery, the proposed algorithm avoided the need for complex machine learning tools and required no previous training. The limitations of the initial experimental setup necessitated the development of a new machinery fault simulator to expand the investigation to include transmission systems. The design, manufacturing and setup of the various subsystems within the new simulator are covered in this manuscript including the mechanical, hydraulic and control subsystems. To ensure that the new simulator has successfully met its design objectives, extensive data collection and analysis has been completed and is presented in this thesis. The results confirmed that the developed machine truly represents the operation of a simultaneously loaded machine and as such would serve as a research tool for investigating the application of classical fault detection techniques to parallel machines in non-stationary operation.Master's These

Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154104/1/kampfner1996.pd

Domain knowledge-informed Synthetic fault sample generation with Health Data Map for cross-domain Planetary Gearbox Fault Diagnosis

Extensive research has been conducted on fault diagnosis of planetary gearboxes using vibration signals and deep learning (DL) approaches. However, DL-based methods are susceptible to the domain shift problem caused by varying operating conditions of the gearbox. Although domain adaptation and data synthesis methods have been proposed to overcome such domain shifts, they are often not directly applicable in real-world situations where only healthy data is available in the target domain. To tackle the challenge of extreme domain shift scenarios where only healthy data is available in the target domain, this paper proposes two novel domain knowledge-informed data synthesis methods utilizing the health data map (HDMap). The two proposed approaches are referred to as scaled CutPaste and FaultPaste. The HDMap is used to physically represent the vibration signal of the planetary gearbox as an image-like matrix, allowing for visualization of fault-related features. CutPaste and FaultPaste are then applied to generate faulty samples based on the healthy data in the target domain, using domain knowledge and fault signatures extracted from the source domain, respectively. In addition to generating realistic faults, the proposed methods introduce scaling of fault signatures for controlled synthesis of faults with various severity levels. A case study is conducted on a planetary gearbox testbed to evaluate the proposed approaches. The results show that the proposed methods are capable of accurately diagnosing faults, even in cases of extreme domain shift, and can estimate the severity of faults that have not been previously observed in the target domain.Comment: Under review / added arXiv identifie

Development of novel gearbox lubrication condition monitoring sensors in the context of wind turbine gearboxes

Wind power has become established as an alternative power source that forms a significant proportion of national energy generation. An increasing proportion of turbines is being constructed offshore to exploit higher average wind speeds and to avoid development issues associated with onshore wind farms. Isolated locations and unpredictable weather conditions lead to increased access costs for operators when conducting scheduled and unscheduled maintenance and repairs. This has increased interest in condition monitoring systems which can track the current state of components within a wind turbine and provide operators with predicted future trends. Asset management can be improved through condition based maintenance regimes and preventative repairs. Development of novel condition monitoring systems that can accurately predict incipient damage can optimise operational performance and reduce the overall level of wind turbine generation costs. The work described in this thesis presents the development of novel sensors that may be applied to monitor wind turbine gearboxes, a component that experiences relatively high failure rates and causes considerable turbine downtime. Current systems and technology that may be adapted for use in wind turbine condition monitoring are evaluated. Lubrication related monitoring systems have been identified as an area that could be improved and are divided into those that track liberated wear material suspended in the lubricant and those that assess the state of the lubricant itself. This study presents two novel lubrication based gearbox monitoring sensors that potentially offer a low cost solution for continuous data capture. The first demonstrates the potential for active pixel sensors such as those found in digital cameras to capture images of wear particles within gearbox lubricants. Particle morphology was tracked in this system, allowing the type of particles to be correlated with the type of wear that is generated and a potential source. The second sensor uses a targeted form of infra-red absorption spectroscopy to track changes in the lubricant chemistry due to the increase in acidity. Ensuring the lubricant is functioning correctly decreases component stress and fatigue, reducing maintenance requirements.Wind power has become established as an alternative power source that forms a significant proportion of national energy generation. An increasing proportion of turbines is being constructed offshore to exploit higher average wind speeds and to avoid development issues associated with onshore wind farms. Isolated locations and unpredictable weather conditions lead to increased access costs for operators when conducting scheduled and unscheduled maintenance and repairs. This has increased interest in condition monitoring systems which can track the current state of components within a wind turbine and provide operators with predicted future trends. Asset management can be improved through condition based maintenance regimes and preventative repairs. Development of novel condition monitoring systems that can accurately predict incipient damage can optimise operational performance and reduce the overall level of wind turbine generation costs. The work described in this thesis presents the development of novel sensors that may be applied to monitor wind turbine gearboxes, a component that experiences relatively high failure rates and causes considerable turbine downtime. Current systems and technology that may be adapted for use in wind turbine condition monitoring are evaluated. Lubrication related monitoring systems have been identified as an area that could be improved and are divided into those that track liberated wear material suspended in the lubricant and those that assess the state of the lubricant itself. This study presents two novel lubrication based gearbox monitoring sensors that potentially offer a low cost solution for continuous data capture. The first demonstrates the potential for active pixel sensors such as those found in digital cameras to capture images of wear particles within gearbox lubricants. Particle morphology was tracked in this system, allowing the type of particles to be correlated with the type of wear that is generated and a potential source. The second sensor uses a targeted form of infra-red absorption spectroscopy to track changes in the lubricant chemistry due to the increase in acidity. Ensuring the lubricant is functioning correctly decreases component stress and fatigue, reducing maintenance requirements

Design and Development of Sensor Integrated Robotic Hand

Most of the automated systems using robots as agents do use few sensors according to the need. However, there are situations where the tasks carried out by the end-effector, or for that matter by the robot hand needs multiple sensors. The hand, to make the best use of these sensors, and behave autonomously, requires a set of appropriate types of sensors which could be integrated in proper manners. The present research work aims at developing a sensor integrated robot hand that can collect information related to the assigned tasks, assimilate there correctly and then do task action as appropriate. The process of development involves selection of sensors of right types and of right specification, locating then at proper places in the hand, checking their functionality individually and calibrating them for the envisaged process. Since the sensors need to be integrated so that they perform in the desired manner collectively, an integration platform is created using NI PXIe-1082. A set of algorithm is developed for achieving the integrated model. The entire process is first modelled and simulated off line for possible modification in order to ensure that all the sensors do contribute towards the autonomy of the hand for desired activity. This work also involves design of a two-fingered gripper. The design is made in such a way that it is capable of carrying out the desired tasks and can accommodate all the sensors within its fold. The developed sensor integrated hand has been put to work and its performance test has been carried out. This hand can be very useful for part assembly work in industries for any shape of part with a limit on the size of the part in mind. The broad aim is to design, model simulate and develop an advanced robotic hand. Sensors for pick up contacts pressure, force, torque, position, surface profile shape using suitable sensing elements in a robot hand are to be introduced. The hand is a complex structure with large number of degrees of freedom and has multiple sensing capabilities apart from the associated sensing assistance from other organs. The present work is envisaged to add multiple sensors to a two-fingered robotic hand having motion capabilities and constraints similar to the human hand. There has been a good amount of research and development in this field during the last two decades a lot remains to be explored and achieved. The objective of the proposed work is to design, simulate and develop a sensor integrated robotic hand. Its potential applications can be proposed for industrial environments and in healthcare field. The industrial applications include electronic assembly tasks, lighter inspection tasks, etc. Application in healthcare could be in the areas of rehabilitation and assistive techniques. The work also aims to establish the requirement of the robotic hand for the target application areas, to identify the suitable kinds and model of sensors that can be integrated on hand control system. Functioning of motors in the robotic hand and integration of appropriate sensors for the desired motion is explained for the control of the various elements of the hand. Additional sensors, capable of collecting external information and information about the object for manipulation is explored. Processes are designed using various software and hardware tools such as mathematical computation MATLAB, OpenCV library and LabVIEW 2013 DAQ system as applicable, validated theoretically and finally implemented to develop an intelligent robotic hand. The multiple smart sensors are installed on a standard six degree-of-freedom industrial robot KAWASAKI RS06L articulated manipulator, with the two-finger pneumatic SHUNK robotic hand or designed prototype and robot control programs are integrated in such a manner that allows easy application of grasping in an industrial pick-and-place operation where the characteristics of the object can vary or are unknown. The effectiveness of the actual recommended structure is usually proven simply by experiments using calibration involving sensors and manipulator. The dissertation concludes with a summary of the contribution and the scope of further work

30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017)

Proceedings of COMADEM 201

Create Cost Effective Post Processing Techniques for Multiple Measured and Simulated Components of CVT Transmissions

The automotive industry requires continuous innovation in order to fight the high competitiveness in this sector. More than ever, fuel economy, low emissions and comfort are the main goals when designing a vehicle. Continuously Variable Transmissions (CVT) are a type of transmissions that meet with those features and it can be the future of automatic transmissions. The presented dissertation was developed during an internship in a company, specialist in the development and production of CVT transmissions, designated by Punch Powertrain NV, located in Sint-Truiden, Belgium. The work was incorporated in the Research and Development (R&D) department, in the team of simulation, where it was possible to enhance the academic experience. This work is based on a need to post-process the results of several measured and simulated scenarios. Firstly, it was proposed to analyse the interference between the components of a hydraulic block. After the block is simulated individually, the inside walls can deform and it is important to analyse if there is interference with the movable components. Secondly, there are corrections done on gears. These corrections are evaluated through gear measurements, which need to be processed to determine if the modifications are within the nominal parameters. The last task was to analyse exported data from road load tests. In each transmission, five accelerometers are installed that record the loads subjected in the three coordinates. These files are read and, then, processed using an algorithm of a counting method, that can predict the cycles of each accelerometer for the different loads. All results are validated by the team leader and the specialists of each field. In the end, the internship allowed to increase the knowledge obtained from the Master’s.A indústria automóvel exige uma inovação contínua, de forma a combater a elevada competitividade neste setor. Mais do que nunca, economia de combustível, baixas emissões e conforto são as principais características na hora de desenhar um veículo. Transmissões Continuamente Variáveis (CVT) são um tipo de transmissão que cumpre esses objetivos e pode ser o futuro das transmissões automáticas. A presente dissertação foi desenvolvida durante um estágio numa empresa especialista no desenvolvimento e produção de transmissões CVT, com o nome de Punch Powertrain NV e localizada em Sint-Truiden, Bélgica. O trabalho foi inserido no departamento de Inovação e Desenvolvimento (I&D), na equipa de simulação, onde foi possível enriquecer a experiência académica. Este trabalho teve por base a necessidade de pós-processar os resultados de diversos cenários medidos e simulados. Em primeiro lugar, foi proposto analisar a interferência entre os componentes de um bloco hidráulico. Depois do bloco ser simulado individualmente, as paredes interiores podem deformar e é importante analisar se existe interferência com as componentes móveis. Em segundo lugar, existem correções feitas em rodas dentadas, para que possam trabalhar corretamente. Então, estas correções são analisadas através de medições, que precisam de ser processadas para determinar se as modificações estão dentro dos parâmetros nominais. A última tarefa foi analisar informação exportada dos testes de carga na estrada. Em cada transmissão, são instalados cinco acelerómetros que registam as cargas submetidas nas três coordenadas. Esses ficheiros são lidos e, depois, processados usando um algoritmo de contagem, que consegue prever os ciclos de cada acelerómetro para as diferentes cargas. Todos os resultados são validados pelo líder de equipa e pelos especialistas de cada área. No final, o estágio permitiu aumentar o conhecimento obtido durante o mestrado