A Similarity-Based Prognostics Approach for Remaining Useful Life Prediction

Physics-based and data-driven models are the two major prognostic approaches in the literature with their own advantages and disadvantages. This paper presents a similarity-based data-driven prognostic methodology and efficiency analysis study on remaining useful life estimation results. A similarity-based prognostic model is modified to employ the most similar training samples for RUL estimations on each time instance. The presented model is tested on; Virkler’s fatigue crack growth dataset, a drilling process degradation dataset, and a sliding chair degradation of a turnout system dataset. Prediction performances are compared utilizing an evaluation metric. Efficiency analysis of optimization results show that the modified similarity-based model performs better than the original definition

Online Bearing Remaining Useful Life Prediction Based on a Novel Degradation Indicator and Convolutional Neural Networks

In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life (RUL) for REBs are of crucial importance to ensure the reliability and safety of mechanical systems. To tackle this challenge, model-based approaches are often limited by the complexity of mathematical modeling. Conventional data-driven approaches, on the other hand, require massive efforts to extract the degradation features and construct health index. In this paper, a novel online data-driven framework is proposed to exploit the adoption of deep convolutional neural networks (CNN) in predicting the RUL of bearings. More concretely, the raw vibrations of training bearings are first processed using the Hilbert-Huang transform (HHT) and a novel nonlinear degradation indicator is constructed as the label for learning. The CNN is then employed to identify the hidden pattern between the extracted degradation indicator and the vibration of training bearings, which makes it possible to estimate the degradation of the test bearings automatically. Finally, testing bearings' RULs are predicted by using a $\epsilon$-support vector regression model. The superior performance of the proposed RUL estimation framework, compared with the state-of-the-art approaches, is demonstrated through the experimental results. The generality of the proposed CNN model is also validated by transferring to bearings undergoing different operating conditions

Development of the Integrated Model of the Automotive Product Quality Assessment

Issues on building an integrated model of the automotive product quality assessment are studied herein basing on widely applicable methods and models of the quality assessment. A conceptual model of the automotive product quality system meeting customer requirements has been developed. Typical characteristics of modern industrial production are an increase in the production dynamism that determines the product properties; a continuous increase in the volume of information required for decision-making, an increased role of knowledge and high technologies implementing absolutely new scientific and technical ideas. To solve the problem of increasing the automotive product quality, a conceptual structural and hierarchical model is offered to ensure its quality as a closed system with feedback between the regulatory, manufacturing, and information modules, responsible for formation of the product quality at all stages of its life cycle. The three module model of the system of the industrial product quality assurance is considered to be universal and to give the opportunity to explore processes of any complexity while solving theoretical and practical problems of the quality assessment and prediction for products for various purposes, including automotive

Stochastic RUL calculation enhanced with TDNN-based IGBT failure modeling

Power electronics are widely used in the transport and energy sectors. Hence, the reliability of these power electronic components is critical to reducing the maintenance cost of these assets. It is vital that the health of these components is monitored for increasing the safety and availability of a system. The aim of this paper is to develop a prognostic technique for estimating the remaining useful life (RUL) of power electronic components. There is a need for an efficient prognostic algorithm that is embeddable and able to support on-board real-time decision-making. A time delay neural network (TDNN) is used in the development of failure modes for an insulated gate bipolar transistor (IGBT). Initially, the time delay neural network is constructed from training IGBTs' ageing samples. A stochastic process is performed for the estimation results to compute the probability of the health state during the degradation process. The proposed TDNN fusion with a statistical approach benefits the probability distribution function by improving the accuracy of the results of the TDDN in RUL prediction. The RUL (i.e., mean and confidence bounds) is then calculated from the simulation of the estimated degradation states. The prognostic results are evaluated using root mean square error (RMSE) and relative accuracy (RA) prognostic evaluation metrics

The State of the Art in Fuel Cell Condition Monitoring and Maintenance

Fuel cell vehicles are considered to be a viable solution to problems such as carbon emissions and fuel shortages for road transport. Proton Exchange Membrane (PEM) Fuel Cells are mainly used in this purpose because they can run at low temperatures and have a simple structure. Yet to make this technology commercially viable, there are still many hurdles to overcome. Apart from the high cost of fuel cell systems, high maintenance costs and short lifecycle are two main issues need to be addressed. The main purpose of this paper is to review the issues affecting the reliability and lifespan of fuel cells and present the state of the art in fuel cell condition monitoring and maintenance. The Structure of PEM fuel cell is introduced and examples of its application in a variety of applications are presented. The fault modes including membrane flooding/drying, fuel/gas starvation, physical defects of membrane, and catalyst poisoning are listed and assessed for their impact. Then the relationship between causes, faults, symptoms and long term implications of fault conditions are summarized. Finally the state of the art in PEM fuel cell condition monitoring and maintenance is reviewed and conclusions are drawn regarding suggested maintenance strategies and the optimal structure for an integrated, cost effective condition monitoring and maintenance management system

Forecasting Russian regional social-economic development and its adaptation to the world economy

The combination of modern economic-geographical methods and methodological approaches is used for the social-economic forecasting. The two-dimensional language reguires the simultaneous description of basic characteristics of the object (system or process) and its distinct positioning on the territory and on the taxonomic scale of the spatial hierarchy. It provides the framework for methodological unity. The spatial analysis includes both the oldest comparative-geographical methods and the modern mathematical. These methods provide an adequate analysis of Russian social-economic regularities. Mathematical statistics was used to reveal the gobal synergetic effects that determine spatial development of the three main types of states, i.e. developed, developing and transitional economies. The paper shows that the fundamental feature of the Russian economy is the abolition of the low prices' system, which determined the overall Russian reality until 1992 and the deep inequilibrium of the supply prices today. This inequilibrium caused the disintegration of the Russian economic space, the local and regional market autonomy, and the flows of goods and passengers under their abrupt decline and redistribution. Under these conditions there are two main development trajectories for Russia: a) an inertia oriented towards the raw material production, with limited defense of the Russian market in the coordination with the WTO principles; b) an orientation towards innovational activities without a refuse from the support of the traditional exports and import substitute industries (taking into account their economic efficiency). The paper discusses mostly the second trajectory.

A stable and accurate control-volume technique based on integrated radial basis function networks for fluid-flow problems

Radial basis function networks (RBFNs) have been widely used in solving partial differential equations as they are able to provide fast convergence. Integrated RBFNs have the ability to avoid the problem of reduced convergence-rate caused by differentiation. This paper is concerned with the use of integrated RBFNs in the context of control-volume discretisations for the simulation of fluid-flow problems. Special attention is given to (i) the development of a stable high-order upwind scheme for the convection term and (ii) the development of a local high-order approximation scheme for the diffusion term. Benchmark problems including the lid-driven triangular-cavity flow are employed to validate the present technique. Accurate results at high values of the Reynolds number are obtained using relatively-coarse grids

Introducing monitoring and automation in cartilage tissue engineering, toward controlled clinical translation

The clinical application of tissue engineered products requires to be tightly connected with the possibility to control the process, assess graft quality and define suitable release criteria for implantation. The aim of this work is to establish techniques to standardize and control the in vitro engineering of cartilage grafts. The work is organized in three sub-projects: first a method to predict cell proliferation capacity was studied, then an in line technique to monitor the draft during in vitro culture was developed and, finally, a culture system for the reproducible production of engineered cartilage was designed and validated. Real-time measurements of human chondrocyte heat production during in vitro proliferation. Isothermal microcalorimetry (IMC) is an on-line, non-destructive and high resolution technique. In this project we aimed to verify the possibility to apply IMC to monitor the metabolic activity of primary human articular chondrocytes (HAC) during their in vitro proliferation. Indeed, currently, many clinically available cell therapy products for the repair of cartilage lesions involve a process of in vitro cell expansion. Establishing a model system able to predict the efficiency of this lengthy, labor-intensive, and challenging to standardize step could have a great potential impact on the manufacturing process. In this study an optimized experimental set up was first established, to reproducible acquire heat flow data; then it was demonstrated that the HAC proliferation within the IMC-based model was similar to proliferation under standard culture conditions, verifying its relevance for simulating the typical cell culture application. Finally, based on the results from 12 independent donors, the possible predictive potential of this technique was assessed. Online monitoring of oxygen as a non-destructive method to quantify cells in engineered 3D tissue constructs. This project aimed at assessing a technique to monitor graft quality during production and/or at release. A quantitative method to monitor the cells number in a 3D construct, based on the on-line measurement of the oxygen consumption in a perfusion based bioreactor system was developed. Oxygen levels dissolved in the medium were monitored on line, by two chemo-optic flow-through micro-oxygen sensors connected at the inlet and the outlet of the bioreactor scaffold chamber. A destructive DNA assay served to quantify the number of cells at the end of the culture. Thus the oxygen consumption per cell could be calculated as the oxygen drop across the perfused constructs at the end of the culture period and the number of cells quantified by DNA. The method developed would allow to non-invasively monitoring in real time the number of chondrocytes on the scaffold. Bioreactor based engineering of large-scale human cartilage grafts for joint resurfacing. The aim of this project was to upscale the size of engineered human cartilage grafts. The main aim of this project consisted in the design and prototyping of a direct perfusion bioreactor system, based on fluidodynamic models (realized in collaboration with the Institute for Bioengineering of Catalonia, Spain), able to guarantee homogeneous seeding and culture conditions trough the entire scaffold surface. The system was then validated and the capability to reproducibly support the process of tissue development was tested by histological, biochemical and biomechanical assays. Within the same project the automation of the designed scaled up bioreactor system, thought as a stand alone system, was proposed. A prototype was realized in collaboration with Applikon Biotechnology BV, The Netherlands. The developed system allows to achieve within a closed environment both cell seeding and culture, controlling some important environmental parameters (e.g. temperature, CO2 and O2 tension), coordinating the medium flow and tracking culture development. The system represents a relevant step toward process automation in tissue engineering and, as previously discussed, enhancing the automation level is an important requirement in order to move towards standardized protocols of graft generation for the clinical practice. These techniques will be critical towards a controlled and standardized procedure for clinical implementation of tissue engineering products and will provide the basis for controlled in vitro studies on cartilage development. Indeed the resulting methods have already been integrated in a streamlined, controlled, bioreactor based protocol for the in vitro production of up scaled engineered cartilage drafts. Moreover the techniques described will serve as the foundation for a recently approved Collaborative Project funded by the European Union, having the goal to produce cartilage tissue grafts. In order to reach this goal the research based technologies and processes described in this dissertation will be adapted for GMP compliance and conformance to regulatory guidelines for the production of engineered tissues for clinical use, which will be tested in a clinical trial

Prosthetic Rehabilitation Following Lateral Resection of the Mandible with a Long Cantilever Implant-Supported Fixed Prosthesis: A 3-Year Clinical Report

This clinical report describes the prosthetic management of the surgical reconstruction of a patient after mandibular resection. Complete oral rehabilitation was achieved with a maxillary complete denture and a mandibular implant-supported fixed prosthesis with a custom titanium framework and a long unilateral cantilever