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.

Methodology for Validating Artifact Removal Techniques for Physiological Signals

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.

Morphology and bacterial colonisation of tooth/ceramic restoration interface after different cement excess removal techniques

Objectives: To evaluate the influence of different protocols for resin cement removal during cementation on biofilm formation.Methods: Twenty-eight ceramic blocks, which were injected under pressure, were placed over enamel blocks obtained from freshly extracted bovine incisors. The ceramic blocks were cemented to the enamel blocks using a dual-cured resin cement and the excess resin was removed according to the experimental group: TS: Teflon spatula; BR: brush; BR+: brush and polishing; SB+: scalpel blade and polishing. After autoclaving, the samples were colonised by incubation in a sucrose broth suspension standardised with Streptococcus mutans in microaerophilic stove. Specimens were quantitatively analysed for bacterial adherence at the adhesive interface using confocal laser scanning microscopy and counting the colony forming units, and qualitatively analysed using SEM. The roughness (Ra/Rz/RSm) was also analysed. Data were analysed by 1-way ANOVA and Tukey's test (5%).Results: The roughness values ranged from 0.96 to 1.69 mu m for Ra (p > 0.05), from 11.59 to 22.80 mu m for Rz (p = 0.02 < 0.05) and from 293.2 to 534.3 mu m for RSm (p = 0.00). Bacterial adhesion varied between 1,974,000 and 2,814,000 CFU/ml (p = 0.00). Biofilm mean thickness ranged from 0.477 and 0.556 mu m (p > 0.05), whilst the biovolume values were between 0.388 and 0.547 mu m(3)/mu m(2) (p = 0.04). Lower values for roughness, bacterial adhesion, biofilm thickness and biovolume were found with BR, whilst TS presented the highest values for most of the parameters. SEM images confirmed the quantitative values.Conclusions: The restoration margin morphology and interface roughness affects bacterial accumulation. The brush technique promoted less bacterial colonisation at the adhesive interface than did the other removal methods.Clinical significance: The brush technique seems to be a good option for removing the excess resin cement after adhesive cementation in clinical practice, as indicated by its better results with lower bacterial colonisation. (C) 2012 Elsevier Ltd. All rights reserved.

Late removal of retrievable caval filters.

The advent of retrievable caval filters was a game changer in the sense, that the previously irreversible act of implanting a medical device into the main venous blood stream of the body requiring careful evaluation of the pros and cons prior to execution suddenly became a "reversible" procedure where potential hazards in the late future of the patient lost most of their weight at the time of decision making. This review was designed to assess the rate of success with late retrieval of so called retrievable caval filters in order to get some indication about reasonable implant duration with respect to relatively "easy" implant removal with conventional means, i.e., catheters, hooks and lassos. A PubMed search (www.pubmed.gov) was performed with the search term "cava filter retrieval after 30 days clinical", and 20 reports between 1994 and 2013 dealing with late retrieval of caval filters were identified, covering approximately 7,000 devices with 600 removed filters. The maximal duration of implant reported is 2,599 days and the maximal implant duration of removed filters is also 2,599 days. The maximal duration reported with standard retrieval techniques, i.e., catheter, hook and/or lasso, is 475 days, whereas for the retrievals after this period more sophisticated techniques including lasers, etc. were required. The maximal implant duration for series with 100% retrieval accounts for 84 days, which is equivalent to 12 weeks or almost 3 months. We conclude that retrievable caval filters often become permanent despite the initial decision of temporary use. However, such "forgotten" retrievable devices can still be removed with a great chance of success up to three months after implantation. Conventional percutaneous removal techniques may be sufficient up to sixteen months after implantation whereas more sophisticated catheter techniques have been shown to be successful up to 83 months or more than seven years of implant duration. Tilting, migrating, or misplaced devices should be removed early on, and replaced if indicated with a device which is both, efficient and retrievable.

Development of an online condition monitoring system for slow speed machinery

One of the main challenges of slow speed machinery condition monitoring is that the energy generated from an incipient defect is too weak to be detected by traditional vibration measurements due to its low impact energy. Acoustic emission (AE) measurement is an alternative for this as it has the ability to detect crack initiations or rubbing between moving surfaces. However, AE measurement requires high sampling frequency and consequently huge amount of data are obtained to be processed. It also requires expensive hardware to capture those data, storage and involves signal processing techniques to retrieve valuable information on the state of the machine. AE signal has been utilised for early detection of defects in bearings and gears. This paper presents an online condition monitoring (CM) system for slow speed machinery, which attempts to overcome those challenges. The system incorporates relevant signal processing techniques for slow speed CM which include noise removal techniques to enhance the signal-to-noise and peak-holding down sampling to reduce the burden of massive data handling. The analysis software works under Labview environment, which enables online remote control of data acquisition, real-time analysis, offline analysis and diagnostic trending. The system has been fully implemented on a site machine and contributing significantly to improve the maintenance efficiency and provide a safer and reliable operation.

Seed Longevity of Melaleuca quinquenervia: A Burial Experiment in South Florida

Burial and removal techniques with seed bags were used to examine the viability and longevity of Melaleuca quinquenervia seeds at four field sites representing different soil types and hydrological conditions in South Florida. Seed viability was determined over different burial durations in the soil through a combination of germination tests and 2,3,5-triphenyl- tetrazolium chloride (TTC) treatments. Control seeds kept dry at 25 C in the laboratory maintained same viability of ca. 15% over the 3-year study. In the field, seed viability decreased with increased burial duration.(PDF has 4 pages.)

Colonização bacteriana na região marginal de restaurações cerâmicas: efeito do método de remoção do cimento e do polimento

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Colonização bacteriana na região marginal de restaurações cerâmicas: efeito do método de remoção do cimento e do polimento

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Target Tracking in UWB Multistatic Radars

Detection, localization and tracking of non-collaborative objects moving inside an area is of great interest to many surveillance applications. An ultra- wideband (UWB) multistatic radar is considered as a good infrastructure for such anti-intruder systems, due to the high range resolution provided by the UWB impulse-radio and the spatial diversity achieved with a multistatic configuration. Detection of targets, which are typically human beings, is a challenging task due to reflections from unwanted objects in the area, shadowing, antenna cross-talks, low transmit power, and the blind zones arised from intrinsic peculiarities of UWB multistatic radars. Hence, we propose more effective detection, localization, as well as clutter removal techniques for these systems. However, the majority of the thesis effort is devoted to the tracking phase, which is an essential part for improving the localization accuracy, predicting the target position and filling out the missed detections. Since UWB radars are not linear Gaussian systems, the widely used tracking filters, such as the Kalman filter, are not expected to provide a satisfactory performance. Thus, we propose the Bayesian filter as an appropriate candidate for UWB radars. In particular, we develop tracking algorithms based on particle filtering, which is the most common approximation of Bayesian filtering, for both single and multiple target scenarios. Also, we propose some effective detection and tracking algorithms based on image processing tools. We evaluate the performance of our proposed approaches by numerical simulations. Moreover, we provide experimental results by channel measurements for tracking a person walking in an indoor area, with the presence of a significant clutter. We discuss the existing practical issues and address them by proposing more robust algorithms.

The pre-treatment and pyrolysis of biomass for the production of liquids for fuels and speciality chemicals

Fast pyrolysis of biomass is a significant technology for producing pyrolysis liquids [also known as bio-oil], which contain a number of chemicals. The pyrolysis liquid can be used as a fuel, can be produced solely as a source of chemicals or can have some of the chemicals extracted and the residue used as a fuel. There were two primary objectives of this work. The first was to determine the fast pyrolysis conditions required to maximise the pyrolysis liquid yield from a number of biomass feedstocks. The second objective was to selectively increase the yield of certain chemicals in the pyrolysis liquid by pre-treatment of the feedstock prior to pyrolysis. For a particular biomass feedstock the pyrolysis liquid yield is affected by the reactor process parameters. It has been found that, providing the other process parameters are restricted to the values shown below, reactor temperature is the controlling parameter. The maximum pyrolysis liquid yield and the temperature at which it occurs has been found by a series of pyrolysis experiments over the temperature range 400-600°C. high heating rates > 1000°C/s; pyrolysis vapour residence times <2 seconds; pyrolysis vapour temperatures >400 but <500°C; rapid quenching of the product vapours. Pre-treatment techniques have been devised to modify the chemical composition and/or structure of the biomass in such a way as to influence the chemical composition of the pyrolysis liquid product. The pre-treatments were divided into two groups, those that remove material from the biomass and those which add material to the biomass. Component removal techniques have selectively increased the yield of levoglucosan from 2.45 to 18.58 mf wt.% [dry feedstock basis]. Additive techniques have selectively increased the yield of hydroxyacetaldehyde from 7.26 to 11.63 mf w.% [dry feedstock basis]. Techno-economic assessment has been carried out on an integrated levoglucosan production process [incorporating pre-treatment, pyrolysis and chemical extraction stages] to assess which method of chemical production is the more cost effective. It has been found that it is better to pre-treat the biomass in order to increase the yield of specific chemicals in the pyrolysis liquid and hence improve subsequent chemicals extraction.

Dual-polarization multi-band optical OFDM transmission and transceiver limitations for up to 500 Gb/s uncompensated long-haul links

A number of critical issues for dual-polarization single- and multi-band optical orthogonal-frequency division multiplexing (DPSB/ MB-OFDM) signals are analyzed in dispersion compensation fiber (DCF)-free long-haul links. For the first time, different DP crosstalk removal techniques are compared, the maximum transmission-reach is investigated, and the impact of subcarrier number and high-level modulation formats are explored thoroughly. It is shown, for a bit-error-rate (BER) of 10-3, 2000 km of quaternary phase-shift keying (QPSK) DP-MBOFDM transmission is feasible. At high launched optical powers (LOP), maximum-likelihood decoding can extend the LOP of 40 Gb/s QPSK DPSB- OFDM at 2000 km by 1.5 dB compared to zero-forcing. For a 100 Gb/s DP-MB-OFDM system, a high number of subcarriers contribute to improved BER but at the cost of digital signal processing computational complexity, whilst by adapting the cyclic prefix length the BER can be improved for a low number of subcarriers. In addition, when 16-quadrature amplitude modulation (16QAM) is employed the digital-toanalogue/ analogue-to-digital converter (DAC/ADC) bandwidth is relaxed with a degraded BER; while the 'circular' 8QAM is slightly superior to its 'rectangular' form. Finally, the transmission of wavelength-division multiplexing DP-MB-OFDM and single-carrier DP-QPSK is experimentally compared for up to 500 Gb/s showing great potential and similar performance at 1000 km DCF-free G.652 line. © 2014 Optical Society of America.

Development of a real time Image analysis system for traffic monitoring applications.

Image processing offers unparalleled potential for traffic monitoring and control. For many years engineers have attempted to perfect the art of automatic data abstraction from sequences of video images. This paper outlines a research project undertaken at Napier University by the authors in the field of image processing for automatic traffic analysis. A software based system implementing TRIP algorithms to count cars and measure vehicle speed has been developed by members of the Transport Engineering Research Unit (TERU) at the University. The TRIP algorithm has been ported and evaluated on an IBM PC platform with a view to hardware implementation of the pre-processing routines required for vehicle detection. Results show that a software based traffic counting system is realisable for single window processing. Due to the high volume of data required to be processed for full frames or multiple lanes, system operations in real time are limited. Therefore specific hardware is required to be designed. The paper outlines a hardware design for implementation of inter-frame and background differencing, background updating and shadow removal techniques. Preliminary results showing the processing time and counting accuracy for the routines implemented in software are presented and a real time hardware pre-processing architecture is described.