Assessing the Technical Specifications of Predictive Maintenance: A Case Study of Centrifugal Compressor

Dependability analyses in the design phase are common in IEC 60300 standards to assess the reliability, risk, maintainability, and maintenance supportability of specific physical assets. Reliability and risk assessment uses well-known methods such as failure modes, effects, and criticality analysis (FMECA), fault tree analysis (FTA), and event tree analysis (ETA)to identify critical components and failure modes based on failure rate, severity, and detectability. Monitoring technology has evolved over time, and a new method of failure mode and symptom analysis (FMSA) was introduced in ISO 13379-1 to identify the critical symptoms and descriptors of failure mechanisms. FMSA is used to estimate monitoring priority, and this helps to determine the critical monitoring specifications. However, FMSA cannot determine the effectiveness of technical specifications that are essential for predictive maintenance, such as detection techniques (capability and coverage), diagnosis (fault type, location, and severity), or prognosis (precision and predictive horizon). The paper proposes a novel predictive maintenance (PdM) assessment matrix to overcome these problems, which is tested using a case study of a centrifugal compressor and validated using empirical data provided by the case study company. The paper also demonstrates the possible enhancements introduced by Industry 4.0 technologies.publishedVersio

Reliability of power systems with climate change effects on PV and wind power generation

Concerns over global climate change has led utilities to reduce greenhouse gas (GHG) emissions by decarbonising the power sector. The accelerating rate of climate change is likely to expose a decarbonised power system to climate related stresses. In particular, Photo Voltaic (PV) and wind power generation systems comprise a significant share in the power grid, which is potentially vulnerable to climate change, and therefore may impact the reliability of power systems with their integrations. Typical reliability assessments do not consider the climate effects and related stresses either on the PV or wind power generating systems or at their component levels. Therefore, this thesis investigates and addresses the challenges of reliability assessment of power grid with the interaction of climate changes and renewable power generation systems. As a part of the investigation, the thesis proposes a novel systematic framework to assess the PV system components’ availability with the interaction of future changes in climate. The framework is developed to quantify the climate related stresses on the hierarchical levels of a PV system, which include component, subsystem, PV system and the grid. The framework was formed by considering multiple elements including thermal stress, bathtub curve, ageing and degradation level and operated on Markov chain embedded Monte Carlo simulation. The uniqueness of the framework is its ability to identify the critical components in a PV system that lead to climate-associated failures. Thesis also proposes a comprehensive framework to assess the reliability of a PV and wind power integrated power system accounting climate change impacts by deploying diverse levels of GHG emission scenarios. Uncertainties in the future climate scenarios were established by proposing an advanced stochastic model considering likelihood-based Markov chain method for generating future climate scenario. The proposed model is integrated to the reliability assessment framework to assess realistic impacts on the reliability of a power system. Investigations were suggested the impacts of climate change effects on PV and wind power generation system were true and in quantitative terms PV systems are more vulnerable to climate change effects than wind power generating systems. The climate change related true impacts on PV and wind power generating systems could be mitigated by quantifying change in impacts quantitatively and then systematic replacement of vulnerable sub system components in time before their end of life. Further investigations suggest that IGBTs and capacitors are key components that are more sensitive to thermal stresses of climate change effects resulting a considering impacts on their availability and on the power system reliability with their presence. Further assessments also revealed that the impacts on power system reliability due to the climate change effects on PV and wind power generation system were not uniform over the long run which further emphasises the need of a quantitative and system assessment in order to expose true impacts of climate change on PV and wind power generation system extending to the entire power system reliability. The thesis provides a solid foundation of frameworks required in the quantitative assessment

Software reliability and dependability: a roadmap

Shifting the focus from software reliability to user-centred measures of dependability in complete software-based systems. Influencing design practice to facilitate dependability assessment. Propagating awareness of dependability issues and the use of existing, useful methods. Injecting some rigour in the use of process-related evidence for dependability assessment. Better understanding issues of diversity and variation as drivers of dependability. Bev Littlewood is founder-Director of the Centre for Software Reliability, and Professor of Software Engineering at City University, London. Prof Littlewood has worked for many years on problems associated with the modelling and evaluation of the dependability of software-based systems; he has published many papers in international journals and conference proceedings and has edited several books. Much of this work has been carried out in collaborative projects, including the successful EC-funded projects SHIP, PDCS, PDCS2, DeVa. He has been employed as a consultant t

Review of recent research towards power cable life cycle management

Power cables are integral to modern urban power transmission and distribution systems. For power cable asset managers worldwide, a major challenge is how to manage effectively the expensive and vast network of cables, many of which are approaching, or have past, their design life. This study provides an in-depth review of recent research and development in cable failure analysis, condition monitoring and diagnosis, life assessment methods, fault location, and optimisation of maintenance and replacement strategies. These topics are essential to cable life cycle management (LCM), which aims to maximise the operational value of cable assets and is now being implemented in many power utility companies. The review expands on material presented at the 2015 JiCable conference and incorporates other recent publications. The review concludes that the full potential of cable condition monitoring, condition and life assessment has not fully realised. It is proposed that a combination of physics-based life modelling and statistical approaches, giving consideration to practical condition monitoring results and insulation response to in-service stress factors and short term stresses, such as water ingress, mechanical damage and imperfections left from manufacturing and installation processes, will be key to success in improved LCM of the vast amount of cable assets around the world

Test-retest reliability of time-frequency measures of auditory steady-state responses in patients with schizophrenia and healthy controls.

BackgroundAuditory steady-state response (ASSR) paradigms have consistently demonstrated gamma band abnormalities in schizophrenia at a 40-Hz driving frequency with both electroencephalography (EEG) and magnetoencephalography (MEG). Various time-frequency measures have been used to assess the 40-Hz ASSR, including evoked power, single trial total power, phase-locking factor (PLF), and phase-locking angle (PLA). While both EEG and MEG studies have shown power and PLF ASSR measures to exhibit excellent test-retest reliability in healthy adults, the reliability of these measures in patients with schizophrenia has not been determined.MethodsASSRs were obtained by recording EEG data during presentation of repeated 20-Hz, 30-Hz and 40-Hz auditory click trains from nine schizophrenia patients (SZ) and nine healthy controls (HC) tested on two occasions. Similar ASSR data were collected from a separate group of 30 HC on two to three test occasions. A subset of these HC subjects had EEG recordings during two tasks, passively listening and actively attending to click train stimuli. Evoked power, total power, PLF, and PLA were calculated following Morlet wavelet time-frequency decomposition of EEG data and test-retest generalizability (G) coefficients were calculated for each ASSR condition, time-frequency measure, and subject group.ResultsG-coefficients ranged from good to excellent (> 0.6) for most 40-Hz time-frequency measures and participant groups, whereas 20-Hz G-coefficients were much more variable. Importantly, test-retest reliability was excellent for the various 40-Hz ASSR measures in SZ, similar to reliabilities in HC. Active attention to click train stimuli modestly reduced G-coefficients in HC relative to the passive listening condition.DiscussionThe excellent test-retest reliability of 40-Hz ASSR measures replicates previous EEG and MEG studies. PLA, a relatively new time-frequency measure, was shown for the first time to have excellent reliability, comparable to power and PLF measures. Excellent reliability of 40 Hz ASSR measures in SZ supports their use in clinical trials and longitudinal observational studies

Design diversity: an update from research on reliability modelling

Diversity between redundant subsystems is, in various forms, a common design approach for improving system dependability. Its value in the case of software-based systems is still controversial. This paper gives an overview of reliability modelling work we carried out in recent projects on design diversity, presented in the context of previous knowledge and practice. These results provide additional insight for decisions in applying diversity and in assessing diverseredundant systems. A general observation is that, just as diversity is a very general design approach, the models of diversity can help conceptual understanding of a range of different situations. We summarise results in the general modelling of common-mode failure, in inference from observed failure data, and in decision-making for diversity in development.

Inspection scheduling based onreliability updating of gas turbinewelded structures

This article presents a novel methodology for the inspection scheduling of gas turbine welded structures, based on reliability calculations and overhaul findings. The model was based on a probabilistic crack propagation analysis for welds in a plate and considered the uncertainty in material properties, defect inspection capabilities, weld geometry, and loads. It developed a specific stress intensity factor and an improved first-order reliability method. The proposed routine alleviated the computational cost of stochastic crack propagation analysis, with accuracy. It is useful to achieve an effective design for manufacturing, to develop structural health monitoring applications, and to adapt inspection schedules to airplane fleet experience.We are grateful to the Mechanical Technology Department of ITPAero (R) for supporting and helping us with this study. The invaluable guidance and feedback from Jose Ramon Andujar is recognized with great appreciation