Remaining useful life prediction using elliptical basis function network and Markov Chain

This paper presents a novel method for remaining useful life prediction using the Elliptical Basis Function (EBF) network and a Markov chain. The EBF structure is trained by a modified Expectation-Maximization (EM) algorithm in order to take into account the missing covariate set. No explicit extrapolation is needed for internal covariates while a Markov chain is constructed to represent the evolution of external covariates in the study. The estimated external and the unknown internal covariates constitute an incomplete covariate set which are then used and analyzed by the EBF network to provide survival information of the asset. It is shown in the case study that the method slightly underestimates the remaining useful life of an asset which is a desirable result for early maintenance decision and resource planning.

Using Web 2.0 tools to facilitate knowledge transfer in complex organisational environments : a primer

An often neglected but well recognised aspect of successful engineering asset management is the achievement of co-operation and collaboration between various occupational, functional and hierarchical levels present within complex technical environments. Engineering and technical contexts have been well documented for the presence of highly cohesive groups based around around functional or role orientations. However while highly cohesive groups are potentially advantageous they are also often correlated with the emergence of knowledge and information silos based around those same functional or occupational clusters. Improved collaboration and co-operation between groups has been demonstrated to result in a number of positive outcomes at an individual, group and organisational level. Example outcomes include an increased capacity for problem solving, improved responsiveness and adaptation to organisational crises, higher morale and an increased ability to leverage workforce capability. However, an essential challenge for organisations wishing to overcome informational silos is to implement mechanisms that facilitate, encourage and sustain interactions between otherwise disconnected groups. This paper reviews the ability of Web 2.0 technologies and mobile computing devices to facilitate and encourage knowledge sharing between “silo’d” groups. Commonly available tools such as Facebook, Twitter, Blogs, Wiki’s and others will be reviewed in relation to their applicability, functionality and ease-of-use by engineering and technical personnel. The paper also documents three case examples of engineering organisations that have successfully employed Web 2.0 to achieve superior knowledge management. With a number of clear recommendations he paper is an essential starting point for any organization looking at the use of new generation technologies for achieving the significant outcomes associated with knowledge transfer.

Using Web 2.0 tools to facilitate knowledge transfer in complex organisational environments : a primer

An often neglected but well recognised aspect of successful engineering asset management is the achievement of co-operation and collaboration between various occupational, functional and hierarchical levels present within complex technical environments. Engineering and technical contexts have been well documented for the presence of highly cohesive groups based around around functional or role orientations. However while highly cohesive groups are potentially advantageous they are also often correlated with the emergence of knowledge and information silos based around those same functional or occupational clusters. Improved collaboration and co-operation between groups has been demonstrated to result in a number of positive outcomes at an individual, group and organisational level. Example outcomes include an increased capacity for problem solving, improved responsiveness and adaptation to organisational crises, higher morale and an increased ability to leverage workforce capability. However, an essential challenge for organisations wishing to overcome informational silos is to implement mechanisms that facilitate, encourage and sustain interactions between otherwise disconnected groups. This paper reviews the ability of Web 2.0 technologies and mobile computing devices to facilitate and encourage knowledge sharing between “silo’d” groups. Commonly available tools such as Facebook, Twitter, Blogs, Wiki’s and others will be reviewed in relation to their applicability, functionality and ease-of-use by engineering and technical personnel. The paper also documents three case examples of engineering organisations that have successfully employed Web 2.0 to achieve superior knowledge management. With a number of clear recommendations the paper is an essential starting point for any organization looking at the use of new generation technologies for achieving the significant outcomes associated with knowledge transfer.

Research project for managing skid resistance is on the road

In December 2006, the Engineering and Technology Group of Queensland’s Department of Main Roads entered into a three-year skid resistance management research project with QUT Faculty of Built Environment and Engineering researchers and the QUT-based CRC for Integrated Engineering Asset Management (CIEAM). CIEAM undertakes a broad range of asset management research in the areas of defence, utilities, transportation and industrial processes. “The research project is an important activity of Main Roads’ Skid Resistance Management Plan published in June 2006.” said Main Roads project leader Mr Justin Weligamage. “The intended project output is a decision-support model for use by Road Asset Managers throughout a road network. The research objective is to enable road asset managers to better manage the surfacing condition of the road asset with specific focus on skid resistance,” said QUT project leader Professor Arun Kumar. The research project will review existing skid resistance investigatory levels, develop a risk-based method to establish skid resistance investigatory levels and improve the decision support methodology in order to minimise crashes. The new risk-based approach will be used to identify locations on the Queensland state-controlled road network that may have inadequate skid resistance. Once a high risk site is identified, the appropriate remedial action will be decided on. This approach will allow road asset managers to target optimal remedial actions, reducing the incidence and severity of crashes where inadequate skid resistance is a contributing cause.

Thin film solar cells based on CU2ZnSnS4 absorber

Cu2ZnSnS4 (CZTS) is considered to be one of the most promising light absorbing materials for low cost, high efficiency thin film solar cells. Compared to conventional CuIn(S, Se)2 (CIS) and Cu(InGa)(S,Se)2 (CIGS) as well as CdTe light absorber, CZTS is only composed of earth-abundant non-toxic elements, ensuring the price competitiveness of this kind of solar cell in the future PV market. However, the research in this area is very limited compared to CIS and CIGS. Detailed studies of both the material and the device are rare, which significantly restricts the development in this area. This paper reviews the progress in the research field of CZTS, particularly the methods which were employed to prepare CZTS absorber material.

Identifying differences in wet and dry road crashes using data mining

It is commonly accepted that wet roads have higher risk of crash than dry roads; however, providing evidence to support this assumption presents some difficulty. This paper presents a data mining case study in which predictive data mining is applied to model the skid resistance and crash relationship to search for discernable differences in the probability of wet and dry road segments having crashes based on skid resistance. The models identify an increased probability of wet road segments having crashes for mid-range skid resistance values.

Vibration of L-shaped plates under a deterministic force or moment excitation : a case of statistical energy analysis application

Analytical and closed form solutions are presented in this paper for the vibration response of an L-shaped plate under a point force or a moment excitation. Inter-relationships between wave components of the source and the receiving plates are clearly defined. Explicit expressions are given for the quadratic quantities such as input power, energy flow and kinetic energy distributions of the L-shaped plate. Applications of statistical energy analysis (SEA) formulation in the prediction of the vibration response of finite coupled plate structures under a single deterministic forcing are examined and quantified. It is found that the SEA method can be employed to predict the frequency averaged vibration response and energy flow of coupled plate structures under a deterministic force or moment excitation when the structural system satisfies the following conditions: (1) the coupling loss factors of the coupled subsystems are known; (2) the source location is more than a quarter of the plate bending wavelength away from the source plate edges in the point force excitation case, or is more than a quarter wavelength away from the pair of source plate edges perpendicular to the moment axis in the moment excitation case due to the directional characteristic of moment excitations. SEA overestimates the response of the L-shaped plate when the source location is less than a quarter bending wavelength away from the respective plate edges owing to wave coherence effect at the plate boundary

Development of a diagnostic tool for condition monitoring of rotating machinery

This paper presents an overview of the CRC for Infrastructure and Engineering Asset Management (CIEAM)’s rotating machine health monitoring project and the status of the research progress. The project focuses on the development of a comprehensive diagnostic tool for condition monitoring and systematic analysis of rotating machinery. Particularly attention focuses on the machine health monitoring of diesel engines, compressors and pumps by using acoustic emission and vibration-based monitoring techniques. The paper also provides a brief summary of the work done by the three main research collaborating partners in the project, namely, Queensland University of Technology (QUT), Curtin University of Technology (CUT) and the University of Western Australia (UWA). Preliminary test and analysis results from this work are also reported in the paper

A grouping model for distributed pipeline assets maintenance decision

Distributed pipeline assets systems are crucial to society. The deterioration of these assets and the optimal allocation of limited budget for their maintenance correspond to crucial challenges for water utility managers. Decision makers should be assisted with optimal solutions to select the best maintenance plan concerning available resources and management strategies. Much research effort has been dedicated to the development of optimal strategies for maintenance of water pipes. Most of the maintenance strategies are intended for scheduling individual water pipe. Consideration of optimal group scheduling replacement jobs for groups of pipes or other linear assets has so far not received much attention in literature. It is a common practice that replacement planners select two or three pipes manually with ambiguous criteria to group into one replacement job. This is obviously not the best solution for job grouping and may not be cost effective, especially when total cost can be up to multiple million dollars. In this paper, an optimal group scheduling scheme with three decision criteria for distributed pipeline assets maintenance decision is proposed. A Maintenance Grouping Optimization (MGO) model with multiple criteria is developed. An immediate challenge of such modeling is to deal with scalability of vast combinatorial solution space. To address this issue, a modified genetic algorithm is developed together with a Judgment Matrix. This Judgment Matrix is corresponding to various combinations of pipe replacement schedules. An industrial case study based on a section of a real water distribution network was conducted to test the new model. The results of the case study show that new schedule generated a significant cost reduction compared with the schedule without grouping pipes.

Structural reliability prediction of a steel bridge element using Dynamic Object Oriented Bayesian Network (DOOBN)

Different from conventional methods for structural reliability evaluation, such as, first/second-order reliability methods (FORM/SORM) or Monte Carlo simulation based on corresponding limit state functions, a novel approach based on dynamic objective oriented Bayesian network (DOOBN) for prediction of structural reliability of a steel bridge element has been proposed in this paper. The DOOBN approach can effectively model the deterioration processes of a steel bridge element and predict their structural reliability over time. This approach is also able to achieve Bayesian updating with observed information from measurements, monitoring and visual inspection. Moreover, the computational capacity embedded in the approach can be used to facilitate integrated management and maintenance optimization in a bridge system. A steel bridge girder is used to validate the proposed approach. The predicted results are compared with those evaluated by FORM method.

Maintenance chain integration using Petri-net enabled multiagent system modeling and implementation approach

Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.

A circuit-breaker restrike diagnostic algorithm using ATP and wavelet transforms

Circuit breaker restrikes are unwanted occurrence, which can ultimately lead to breaker. Before 2008, there was little evidence in the literature of monitoring techniques based on restrike measurement and interpretation produced during switching of capacitor banks and shunt reactor banks. In 2008 a non-intrusive radiometric restrike measurement method, as well a restrike hardware detection algorithm was developed. The limitations of the radiometric measurement method are a band limited frequency response as well as limitations in amplitude determination. Current detection methods and algorithms required the use of wide bandwidth current transformers and voltage dividers. A novel non-intrusive restrike diagnostic algorithm using ATP (Alternative Transient Program) and wavelet transforms is proposed. Wavelet transforms are the most common use in signal processing, which is divided into two tests, i.e. restrike detection and energy level based on deteriorated waveforms in different types of restrike. A ‘db5’ wavelet was selected in the tests as it gave a 97% correct diagnostic rate evaluated using a database of diagnostic signatures. This was also tested using restrike waveforms simulated under different network parameters which gave a 92% correct diagnostic responses. The diagnostic technique and methodology developed in this research can be applied to any power monitoring system with slight modification for restrike detection.

Development of diagnostic and prognostic algorithms from vacuum circuit breaker restrike review and its validation proposal

The CIGRE WGs A3.20 and A3.24 identify the requirements of simulation tools to predict various stresses during the development and operational phases of medium voltage vacuum circuit breaker (VCB) testing. This paper reviews the modelling methodology [13], VCB models and tools to identify future research. It will include the application of the VCB model for the impending failure of a VCB using electro-magnetic-transient-program with diagnostic and prognostic algorithm development. The methodology developed for a VCB degradation model is to modify the dielectric equation to cover a restriking period of more than 1 millimetre.

Group maintenance scheduling : a case study for a pipeline network

This paper presents a group maintenance scheduling case study for a water distributed network. This water pipeline network presents the challenge of maintaining aging pipelines with the associated increases in annual maintenance costs. The case study focuses on developing an effective maintenance plan for the water utility. Current replacement planning is difficult as it needs to balance the replacement needs under limited budgets. A Maintenance Grouping Optimization (MGO) model based on a modified genetic algorithm was utilized to develop an optimum group maintenance schedule over a 20-year cycle. The adjacent geographical distribution of pipelines was used as a grouping criterion to control the searching space of the MGO model through a Judgment Matrix. Based on the optimum group maintenance schedule, the total cost was effectively reduced compared with the schedules without grouping maintenance jobs. This optimum result can be used as a guidance to optimize the current maintenance plan for the water utility.