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.

A brief guide to synchrotron radiation-based microtomography in (structural) geology and rock mechanics

This contribution outlines Synchrotron-based X-ray micro-tomography and its potential use in structural geology and rock mechanics. The paper complements several recent reviews of X-ray microtomography. We summarize the general approach to data acquisition, post-processing as well as analysis and thereby aim to provide an entry point for the interested reader. The paper includes tables listing relevant beamlines, a list of all available imaging techniques, and available free and commercial software packages for data visualization and quantification. We highlight potential applications in a review of relevant literature including time-resolved experiments and digital rock physics. The paper concludes with a report on ongoing developments and upgrades at synchrotron facilities to frame the future possibilities for imaging sub-second processes in centimetre-sized samples.

Time- vs. frequency-domain identification of parametric radiation force models for marine structures at zero speed

The dynamics describing the motion response of a marine structure in waves can be represented within a linear framework by the Cummins Equation. This equation contains a convolution term that represents the component of the radiation forces associated with fluid memory effects. Several methods have been proposed in the literature for the identification of parametric models to approximate and replace this convolution term. This replacement can facilitate the model implementation in simulators and the analysis of motion control designs. Some of the reported identification methods consider the problem in the time domain while other methods consider the problem in the frequency domain. This paper compares the application of these identification methods. The comparison is based not only on the quality of the estimated models, but also on the ease of implementation, ease of use, and the flexibility of the identification method to incorporate prior information related to the model being identified. To illustrate the main points arising from the comparison, a particular example based on the coupled vertical motion of a modern containership vessel is presented.

Direct and quantitative detection of bacteriophage by “hearing” surface detachment using a quartz crystal microbalance

We show that it is possible to detect specifically adsorbed bacteriophage directly by breaking the interactions between proteins displayed on the phage coat and ligands immobilized on the surface of a quartz crystal microbalance (QCM). This is achieved through increasing the amplitude of oscillation of the QCM surface and sensitively detecting the acoustic emission produced when the bacteriophage detaches from the surface. There is no interference from nonspecifically adsorbed phage. The detection is quantitative over at least 5 orders of magnitude and is sensitive enough to detect as few as 20 phage. The method has potential as a sensitive and low-cost method for virus detection.

Direct and quantitative detection of bacteriophage by "hearing" surface detachment using a quartz crystal microbalance

We show that it is possible to detect specifically adsorbed bacteriophage directly by breaking the interactions between proteins displayed on the phage coat and ligands immobilized on the surface of a quartz crystal microbalance (QCM). This is achieved through increasing the amplitude of oscillation of the QCM surface and sensitively detecting the acoustic emission produced when the bacteriophage detaches from the surface. There is no interference from nonspecifically adsorbed phage. The detection is quantitative over at least 5 orders of magnitude and is sensitive enough to detect as few as 20 phage. The method has potential as a sensitive and low-cost method for virus detection.

Genome-wide SNP detection, validation, and development of an 8K SNP array for apple

As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC) has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica) breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of 'Golden Delicious', SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional), and genomic selection in apple.

Protocol : A highly sensitive RT-PCR method for detection and quantification of microRNAs

MicroRNAs (miRNAs) are a class of small non-coding RNAs with a critical role in development and environmental responses. Efficient and reliable detection of miRNAs is an essential step towards understanding their roles in specific cells and tissues. However, gel-based assays currently used to detect miRNAs are very limited in terms of throughput, sensitivity and specificity. Here we provide protocols for detection and quantification of miRNAs by RT-PCR. We describe an end-point and real-time looped RT-PCR procedure and demonstrate detection of miRNAs from as little as 20 pg of plant tissue total RNA and from total RNA isolated from as little as 0.1 l of phloem sap. In addition, we have developed an alternative real-time PCR assay that can further improve specificity when detecting low abundant miRNAs. Using this assay, we have demonstrated that miRNAs are differentially expressed in the phloem sap and the surrounding vascular tissue. This method enables fast, sensitive and specific miRNA expression profiling and is suitable for facilitation of high-throughput detection and quantification of miRNA expression.

Macroscopic fundamental diagram for Brisbane, Australia: empirical findings on network partitioning and incident detection

The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow, and the existence with dynamic features was confirmed in congested urban network in downtown Yokohama with real data set. Since the MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. However, limited works have been reported on real world example from signalised arterial network. This paper fuses data from multiple sources (Bluetooth, Loops and Signals) and presents a framework for the development of the MFD for Brisbane, Australia. Existence of the MFD in Brisbane arterial network is confirmed. Different MFDs (from whole network and several sub regions) are evaluated to discover the spatial partitioning for network performance representation. The findings confirmed the usefulness of appropriate network partitioning for traffic monitoring and incident detections. The discussion addressed future research directions.

The ranking based constrained document clustering method and its application to social event detection

With the growing size and variety of social media files on the web, it’s becoming critical to efficiently organize them into clusters for further processing. This paper presents a novel scalable constrained document clustering method that harnesses the power of search engines capable of dealing with large text data. Instead of calculating distance between the documents and all of the clusters’ centroids, a neighborhood of best cluster candidates is chosen using a document ranking scheme. To make the method faster and less memory dependable, the in-memory and in-database processing are combined in a semi-incremental manner. This method has been extensively tested in the social event detection application. Empirical analysis shows that the proposed method is efficient both in computation and memory usage while producing notable accuracy.

Quantitative stem-loop RT-PCR for detection of microRNAs

Plant microRNAs (miRNAs) are a class of endogenous small RNAs that are essential for plant development and survival. They arise from larger precursor RNAs with a characteristic hairpin structure and regulate gene activity by targeting mRNA transcripts for cleavage or translational repression. Efficient and reliable detection and quantification of miRNA expression has become an essential step in understanding their specific roles. The expression levels of miRNAs can vary dramatically between samples and they often escape detection by conventional technologies such as cloning, northern hybridization and microarray analysis. The stem-loop RT-PCR method described here is designed to detect and quantify mature miRNAs in a fast, specific, accurate and reliable manner. First, a miRNA-specific stem-loop RT primer is hybridized to the miRNA and then reverse transcribed. Next, the RT product is amplified and monitored in real time using a miRNA-specific forward primer and the universal reverse primer. This method enables miRNA expression profiling from as little as 10 pg of total RNA and is suitable for high-throughput miRNA expression analysis.

Radiographer commenting of trauma radiographs : a survey of the benefits, barriers and enablers to participation in an Australian healthcare setting

Introduction Radiographer abnormality detection systems that highlight abnormalities on trauma radiographs (‘red dot’ system) have been operating for more than 30 years. Recently, a number of pitfalls have been identified. These limitations initiated the evolution of a radiographer commenting system, whereby a radiographer provides a brief description of abnormalities identified in emergency healthcare settings. This study investigated radiographers' participation in abnormality detection systems, their perceptions of benefits, barriers and enablers to radiographer commenting, and perceptions of potential radiographer image interpretation services for emergency settings. Methods A cross-sectional survey was implemented. Participants included radiographers from four metropolitan hospitals in Queensland, Australia. Conventional descriptive statistics, histograms and thematic analysis were undertaken. Results Seventy-three surveys were completed and included in the analysis (68% response rate); 30 (41%) of respondents reported participating in abnormality detection in 20% or less of examinations, and 26(36%) reported participating in 80% or more of examinations. Five overarching perceived benefits of radiographer commenting were identified: assisting multidisciplinary teams, patient care, radiographer ability, professional benefits and quality of imaging. Frequently reported perceived barriers included ‘difficulty accessing image interpretation education’, ‘lack of time’ and ‘low confidence in interpreting radiographs’. Perceived enablers included ‘access to image interpretation education’ and ‘support from radiologist colleagues’. Conclusions A range of factors are likely to contribute to the successful implementation of radiographer commenting in addition to abnormality detection in emergency settings. Effective image interpretation education amenable to completion by radiographers would likely prove valuable in preparing radiographers for participation in abnormality detection and commenting systems in emergency settings.

An introduction to radiation protection in medicine

"Combining facets of health physics with medicine, An Introduction to Radiation Protection in Medicine covers the background of the subject and the medical situations where radiation is the tool to diagnose or treat human disease. Encouraging newcomers to the field to properly and efficiently function in a versatile and evolving work setting, it familiarizes them with the particular problems faced during the application of ionizing radiation in medicine. The text builds a fundamental knowledge base before providing practical descriptions of radiation safety in medicine. It covers basic issues related to radiation protection, including the physical science behind radiation protection and the radiobiological basis of radiation protection. The text also presents operational and managerial tools for organizing radiation safety in a medical workplace. Subsequent chapters form the core of the book, focusing on the practice of radiation protection in different medical disciplines. They explore a range of individual uses of ionizing radiation in various branches of medicine, including radiology, nuclear medicine, external beam radiotherapy, and brachytherapy. With contributions from experienced practicing physicists, this book provides essential information about dealing with radiation safety in the rapidly shifting and diverse environment of medicine."--publisher website

Recursive actuator fault detection and diagnosis for emergency landing of UASs

This paper presents a practical recursive fault detection and diagnosis (FDD) scheme for online identification of actuator faults for unmanned aerial systems (UASs) based on the unscented Kalman filtering (UKF) method. The proposed FDD algorithm aims to monitor health status of actuators and provide indication of actuator faults with reliability, offering necessary information for the design of fault-tolerant flight control systems to compensate for side-effects and improve fail-safe capability when actuator faults occur. The fault detection is conducted by designing separate UKFs to detect aileron and elevator faults using a nonlinear six degree-of-freedom (DOF) UAS model. The fault diagnosis is achieved by isolating true faults by using the Bayesian Classifier (BC) method together with a decision criterion to avoid false alarms. High-fidelity simulations with and without measurement noise are conducted with practical constraints considered for typical actuator fault scenarios, and the proposed FDD exhibits consistent effectiveness in identifying occurrence of actuator faults, verifying its suitability for integration into the design of fault-tolerant flight control systems for emergency landing of UASs.

Accelerometer validity and placement for detection of changes in physical activity in dogs under controlled conditions on a treadmill

The objective of the research was to determine the optimal location and method of attachment for accelerometer-based motion sensors, and to validate their ability to differentiate rest and increases in speed in healthy dogs moving on a treadmill. Two accelerometers were placed on a harness between the scapulae of dogs with one in a pouch and one directly attached to the harness. Two additional accelerometers were placed (pouched and not pouched) ventrally on the dog's collar. Data were recorded in 1. s epochs with dogs moving in stages lasting 3. min each on a treadmill: (1) at rest, lateral recumbency, (2) treadmill at 0% slope, 3. km/h, (3) treadmill at 0% slope, 5. km/h, (4) treadmill at 0% slope, 7. km/h, (5) treadmill at 5% slope, 5. km/h, and; (6) treadmill at 5% slope, 7. km/h. Only the harness with the accelerometer in a pouch along the dorsal midline yielded statistically significant increases (P< 0.05) in vector magnitude as walking speed of the dogs increased (5-7. km/h) while on the treadmill. Statistically significant increases in vector magnitude were detected in the dogs as the walking speed increased from 5 to 7. km/h, however, changes in vector magnitude were not detected when activity intensity was increased as a result of walking up a 5% grade. Accelerometers are a valid and objective tool able to discriminate between and monitor different levels of activity in dogs in terms of speed of movement but not in energy expenditure that occurs with movement up hill.

A sensor fault detection and isolation method in interior permanent-magnet synchronous motor drives based on an extended Kalman filter

Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.