A Systematic review of a statistical vacuum circuit breaker model for condition monitoring

Vacuum circuit breaker (VCB) overvoltage failure and its catastrophic failures during shunt reactor switching have been analyzed through computer simulations for multiple reignitions with a statistical VCB model found in the literature. However, a systematic review (SR) that is related to the multiple reignitions with a statistical VCB model does not yet exist. Therefore, this paper aims to analyze and explore the multiple reignitions with a statistical VCB model. It examines the salient points, research gaps and limitations of the multiple reignition phenomenon to assist with future investigations following the SR search. Based on the SR results, seven issues and two approaches to enhance the current statistical VCB model are identified. These results will be useful as an input to improve the computer modeling accuracy as well as the development of a reignition switch model with point-on-wave controlled switching for condition monitoring

Condition monitoring and operational decision making in semiconductor manufacturing

Today, the majority of semiconductor fabrication plants (fabs) conduct equipment preventive maintenance based on statistically-derived time- or wafer-count-based intervals. While these practices have had relative success in managing equipment availability and product yield, the cost, both in time and materials, remains high. Condition-based maintenance has been successfully adopted in several industries, where costs associated with equipment downtime range from potential loss of life to unacceptable affects to companies’ bottom lines. In this paper, we present a method for the monitoring of complex systems in the presence of multiple operating regimes. In addition, the new representation of degradation processes will be used to define an optimization procedure that facilitates concurrent maintenance and operational decision-making in a manufacturing system. This decision-making procedure metaheuristically maximizes a customizable cost function that reflects the benefits of production uptime, and the losses incurred due to deficient quality and downtime. The new degradation monitoring method is illustrated through the monitoring of a deposition tool operating over a prolonged period of time in a major fab, while the operational decision-making is demonstrated using simulated operation of a generic cluster tool.

A new procedure for using envelope analysis for rolling element bearing diagnostics in variable operating conditions

In the field of rolling element bearing diagnostics envelope analysis, and in particular the squared envelope spectrum, have gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of squared envelope spectrum has been extended to cases in which small speed fluctuations occur, maintaining the effectiveness and efficiency that characterize this successful technique. However, the constraint on speed has to be removed completely, making envelope analysis suitable also for speed and load transients, to implement an algorithm valid for all the industrial application. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This paper is aimed at providing and testing a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.

Characteristics of low-speed vehicle run-over events in children : an 11-year review

Objectives: The purpose of this study was to investigate the characteristics associated with fatal and non-fatal low-speed vehicle run-over (LSVRO) events in relation to person, incident and injury characteristics, in order to identify appropriate points for intervention and injury prevention. Methods: Data on all known LSVRO events in Queensland, Australia, over 11 calendar years (1999–2009) were extracted from five different databases representing the continuum of care ( prehospital to fatality) and manually linked. Descriptive and multivariate analyses were used to analyse the sample characteristics in relation to demographics, health service usage, outcomes, incident characteristics, and injury characteristics. Results: Of the 1641 LSVRO incidents, 98.4% (n=1615) were non-fatal, and 1.6% were fatal (n=26). Over half the children required admission to hospital (56%, n=921); mean length of stay was 3.4 days. Younger children aged 0–4 years were more frequently injured, and experienced more serious injuries with worse outcomes. Patterns of injury (injury type and severity), injury characteristics (eg, time of injury, vehicle type, driver of vehicle, incident location), and demographic characteristics (such as socioeconomic status, indigenous status, remoteness), varied according to age group. Almost half (45.6%; n=737) the events occurred outside major cities, and approximately 10% of events involved indigenous children. Parents were most commonly the vehicle drivers in fatal incidents. While larger vehicles such as four-wheel drives (4WD) were most frequently involved in LSVRO events resulting in fatalities, cars were most frequently involved in non-fatal events. Conclusions: This is the first study, to the authors’ knowledge, to analyse the characteristics of fatal and non-fatal LSVRO events in children aged 0–15 years on a state-wide basis. Characteristics of LSVRO events varied with age, thus age-specific interventions are required. Children living outside major cities, and indigenous children, were over-represented in these data. Further research is required to identify the burden of injury in these groups.

Incidence of paediatric fatal and non-fatal low speed vehicle run over events in Queensland, Australia : eleven year analysis

Background The purpose of this study was to estimate the incidence of fatal and non-fatal Low Speed Vehicle Run Over (LSVRO) events among children aged 0–15 years in Queensland, Australia, at a population level. Methods Fatal and non-fatal LSVRO events that occurred in children resident in Queensland over eleven calendar years (1999-2009) were identified using ICD codes, text description, word searches and medical notes clarification, obtained from five health related data bases across the continuum of care (pre-hospital to fatality). Data were manually linked. Population data provided by the Australian Bureau of Statistics were used to calculate crude incidence rates for fatal and non-fatal LSVRO events. Results There were 1611 LSVROs between 1999–2009 (IR = 16.87/100,000/annum). Incidence of non-fatal events (IR = 16.60/100,000/annum) was 61.5 times higher than fatal events (IR = 0.27/100,000/annum). LSVRO events were more common in boys (IR = 20.97/100,000/annum) than girls (IR = 12.55/100,000/annum), and among younger children aged 0–4 years (IR = 21.45/100000/annum; 39% or all events) than older children (5–9 years: IR = 16.47/100,000/annum; 10–15 years IR = 13.59/100,000/annum). A total of 896 (56.8%) children were admitted to hospital for 24 hours of more following an LSVRO event (IR = 9.38/100,000/annum). Total LSVROs increased from 1999 (IR = 14.79/100,000) to 2009 (IR = 18.56/100,000), but not significantly. Over the 11 year period, there was a slight (non –significant) increase in fatalities (IR = 0.37-0.42/100,000/annum); a significant decrease in admissions (IR = 12.39–5.36/100,000/annum), and significant increase in non-admissions (IR = 2.02-12.77/100,000/annum). Trends over time differed by age, gender and severity. Conclusion This is the most comprehensive, population-based epidemiological study on fatal and non-fatal LSVRO events to date. Results from this study indicate that LSVROs incur a substantial burden. Further research is required on the characteristics and risk factors associated with these events, in order to adequately inform injury prevention. Strategies are urgently required in order to prevent these events, especially among young children aged 0-4 years.

Experimental investigations of improved dielectric condition monitoring methods on transformer oil-paper insulation system

Frequency Domain Spectroscopy (FDS) is successfully being used to assess the insulation condition of oil filled power transformers. However, it has to date only been implemented on de-energized transformers, which requires the transformers to be shut down for an extended period which can result in significant costs. To solve this issue, a method of implementing FDS under energized condition is proposed here. A chirp excitation waveform is used to replace the conventional sinusoidal waveform to reduce the measurement time in this method. Investigation of the dielectric response under the influence of a high voltage stress at power frequency is reported based on experimental results. To further understand the insulation ageing process, the geometric capacitance effect is removed to enhance the detection of the ageing signature. This enhancement enables the imaginary part of admittance to be used as a new indicator to assess the ageing status of the insulation.

Systematic literature review of incidence rates of low-speed vehicle run-over incidents in children

Aim: To systematically review the literature investigating the incidence of fatal and or nonfatal low-speed vehicle run-over (LSVRO) incidents in children aged 0–15 years. Methods: The following databases were searched using specific search terms, from their date of conception up to June 2011: Cochrane Library, Medline, CINAHL, Embase, AMI, Sociological Abstracts, ERIC, PsycArticles, PsycInfo, Urban Studies and Planning; Australian Criminology Database; Dissertations and Thesis; Academic Research Library; Social Services Abstracts; Family and Society; Scopus; and Web of Science. A total of 128 articles were identified in the databases (33 found by hand searching). The title and abstract of these were read, and 102 were removed because they were not primary research articles relating to LSVRO-type injuries. Twenty-six articles were assessed against the inclusion (reporting population level incidence rates) and exclusion criteria, 19 of which were excluded, leaving a total of five articles for inclusion in the review. Findings: Five studies were identified that met the inclusion criteria. The incidence rate in nonfatal LSVRO events varied in the range of 7.09 to 14.79 per 100,000 and from 0.63 to 3.2 per 100,000 in fatal events. Discussion: Using International Classification of Diseases codes for classifying fatal or nonfatal LSVRO incidents is problematic as there is no specific code for LSVRO. The current body of research is void of a comprehensive secular population data analysis. Only with an improved spectrum of incidence rates will appropriate evaluation of this problem be possible, and this will inform nursing prevention interventions. The effect of LSVRO incidents is clearly understudied. More research is required to address incidence rates in relation to culture, environment, risk factors, car design, and injury characteristics. Conclusions: Thevlack of nursing research or policy around this area of injury, most often to children, indicates a field of inquiry and policy development that needs attention.

Condition monitoring and rating of bridge components in a rail or road network by using SHM systems within SRP

The safety and performance of bridges could be monitored and evaluated by Structural Health Monitoring (SHM) systems. These systems try to identify and locate the damages in a structure and estimate their severities. Current SHM systems are applied to a single bridge, and they have not been used to monitor the structural condition of a network of bridges. This paper propose a new method which will be used in Synthetic Rating Procedures (SRP) developed by the authors of this paper and utilizes SHM systems for monitoring and evaluating the condition of a network of bridges. Synthetic rating procedures are used to assess the condition of a network of bridges and identify their ratings. As an additional part of the SRP, the method proposed in this paper can continuously monitor the behaviour of a network of bridges and therefore it can assist to prevent the sudden collapses of bridges or the disruptions to their serviceability. The method could be an important part of a bridge management system (BMS) for managers and engineers who work on condition assessment of a network of bridges.

Fault detection of slow speed rolling element bearing with noise removal techniques

Rolling Element Bearings (REBs) are vital components in rotating machineries for providing rotating motion. In slow speed rotating machines, bearings are normally subjected to heavy static loads and a catastrophic failure can cause enormous disruption to production and human safety. Due to its low operating speed the impact energy generated by the rotating elements on the defective components is not sufficient to produce a detectable vibration response. This is further aggravated by the inability of general measuring instruments to detect and process the weak signals at the initiation of the defect accurately. Furthermore, the weak signals are often corrupted by background noise. This is a serious problem faced by maintenance engineers today and the inability to detect an incipient failure of the machine can significantly increases the risk of functional failure and costly downtime. This paper presents the application of noise removal techniques for enhancing the detection capability for slow speed REB condition monitoring. Blind deconvolution (BD) and adaptive line enhancer (ALE) are compared to evaluate their performance in enhancing the source signal with consequential removal of background noise. In the experimental study, incipient defects were seeded on a number of roller bearings and the signals were acquired using acoustic emission (AE) sensor. Kurtosis and modified peak ratio (mPR) were used to determine the detectability of signal corrupted by noise.

Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions

Diagnostics of rolling element bearings involves a combination of different techniques of signal enhancing and analysis. The most common procedure presents a first step of order tracking and synchronous averaging, able to remove the undesired components, synchronous with the shaft harmonics, from the signal, and a final step of envelope analysis to obtain the squared envelope spectrum. This indicator has been studied thoroughly, and statistically based criteria have been obtained, in order to identify damaged bearings. The statistical thresholds are valid only if all the deterministic components in the signal have been removed. Unfortunately, in various industrial applications, characterized by heterogeneous vibration sources, the first step of synchronous averaging is not sufficient to eliminate completely the deterministic components and an additional step of pre-whitening is needed before the envelope analysis. Different techniques have been proposed in the past with this aim: The most widely spread are linear prediction filters and spectral kurtosis. Recently, a new technique for pre-whitening has been proposed, based on cepstral analysis: the so-called cepstrum pre-whitening. Owing to its low computational requirements and its simplicity, it seems a good candidate to perform the intermediate pre-whitening step in an automatic damage recognition algorithm. In this paper, the effectiveness of the new technique will be tested on the data measured on a full-scale industrial bearing test-rig, able to reproduce the harsh conditions of operation. A benchmark comparison with the traditional pre-whitening techniques will be made, as a final step for the verification of the potentiality of the cepstrum pre-whitening.

Fault symptoms of rolling element bearings under variable operating conditions - a multi domain analysis

Diagnostics of rolling element bearings have been traditionally developed for constant operating conditions, and sophisticated techniques, like Spectral Kurtosis or Envelope Analysis, have proven their effectiveness by means of experimental tests, mainly conducted in small-scale laboratory test-rigs. Algorithms have been developed for the digital signal processing of data collected at constant speed and bearing load, with a few exceptions, allowing only small fluctuations of these quantities. Owing to the spreading of condition based maintenance in many industrial fields, in the last years a need for more flexible algorithms emerged, asking for compatibility with highly variable operating conditions, such as acceleration/deceleration transients. This paper analyzes the problems related with significant speed and load variability, discussing in detail the effect that they have on bearing damage symptoms, and propose solutions to adapt existing algorithms to cope with this new challenge. In particular, the paper will i) discuss the implication of variable speed on the applicability of diagnostic techniques, ii) address quantitatively the effects of load on the characteristic frequencies of damaged bearings and iii) finally present a new approach for bearing diagnostics in variable conditions, based on envelope analysis. The research is based on experimental data obtained by using artificially damaged bearings installed on a full scale test-rig, equipped with actual train traction system and reproducing the operation on a real track, including all the environmental noise, owing to track irregularity and electrical disturbances of such a harsh application.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

Diagnostic of Rolling Element Bearings with Envelope Analysis in Non-Stationary Conditions

In the field of rolling element bearing diagnostics, envelope analysis has gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of this technique has been extended to cases in which small speed fluctuations occur, maintaining high effectiveness and efficiency. In order to make this algorithm suitable to all industrial applications, the constraint on speed has to be removed completely. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This chapter presents a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.