Machine condition monitoring and fault diagnosis using spectral analysis techniques

There is need to continuously monitor the conditions of complex, expensive and process-critical machinery in order to detect its incipient breakdown as well as to ensure its high performance and operating safety. Depending on the application, several techniques are available for monitoring the condition of a machine. Vibration monitoring of rotating machinery is considered in this paper so as develop a selfdiagnosis tool for monitoring machines’ conditions. To achieve this a vibration fault simulation rig (VFSR) is designed and constructed so as to simulate and analyze some of the most common vibration signals encountered in rotating machinery. Vibration data are collected from the piezoelectric accelerometers placed at locations that provide rigid vibration transmission to them. Both normal and fault signals are analyzed using the singular value decomposition (SVD) algorithm so as to compute the parameters of the auto regressive moving average (ARMA) models. Machine condition monitoring is then based on the AR or ARMA spectra so as to overcome some of the limitations of the fast Fourier transform (FFT) techniques. Furthermore the estimated AR model parameters and the distribution of the singular values can be used in conjunction with the spectral peaks in making comparison between healthy and faulty conditions. Different fault conditions have been successfully simulated and analyzed using the VFSR in this paper. Results of analysis clearly indicate that this method of analysis can be further developed and used for self-diagnosis, predictive maintenance and intelligent-based monitoring

Nonzero θ13\theta_{13} and Neutrino Masses from Modified Neutrino Mixing Matrix

The nonzero and relatively large $\theta_{13}$ have been reported by Daya Bay, T2K, MINOS, and Double Chooz Collaborations. In order to accommodate the nonzero $\theta_{13}$, we modified the tribimaximal (TB), bimaxima (BM), and democratic (DC) neutrino mixing matrices. From three modified neutrino mixing matrices, two of them (the modified BM and DC mixing matrices) can give nonzero $\theta_{13}$ which is compatible with the result of the Daya Bay and T2K experiments. The modified TB neutrino mixing matrix predicts the value of $\theta_{13}$ greater than the upper bound value of the latest experimental results. By using the modified neutrino mixing matrices and impose an additional assumption that neutrino mass matrices have two zeros texture, we then obtain the neutrino mass in normal hierarchy when $(M_{\nu})_{22}=(M_{\nu})_{33}=0$ for the neutrino mass matrix from the modified TB neutrino mixing matrix and $(M_{\nu})_{11}=(M_{\nu})_{13}=0$ for the neutrino mass matrix from the modified DC neutrino mixing matrix. For these two patterns of neutrino mass matrices, either the atmospheric mass squared difference or the solar mass squared difference can be obtained, but not both of them simultaneously. From four patterns of two zeros texture to be considered on the obtained neutrino mass matrix from the modified BM neutrino mixing matrix, none of them can predict correctly neutrino mass spectrum (normal or inverted hierarchy).Comment: 13 pages, no figure, some references added, and slight revision due to reviewer(s) comments, to be published in IJMP

Machine condition monitoring and fault diagnosis using spectral analysis techniques

There is need to continuously monitor the conditions of complex, expensive and process-critical machinery in order to detect its incipient breakdown as well as to ensure its high performance and operating safety. Depending on the application, several techniques are available for monitoring the condition of a machine. Vibration monitoring of rotating machinery is considered in this paper so as develop a selfdiagnosis tool for monitoring machines’ conditions. To achieve this a vibration fault simulation rig (VFSR) is designed and constructed so as to simulate and analyze some of the most common vibration signals encountered in rotating machinery. Vibration data are collected from the piezoelectric accelerometers placed at locations that provide rigid vibration transmission to them. Both normal and fault signals are analyzed using the singular value decomposition (SVD) algorithm so as to compute the parameters of the auto regressive moving average (ARMA) models. Machine condition monitoring is then based on the AR or ARMA spectra so as to overcome some of the limitations of the fast Fourier transform (FFT) techniques. Furthermore the estimated AR model parameters and the distribution of the singular values can be used in conjunction with the spectral peaks in making comparison between healthy and faulty conditions. Different fault conditions have been successfully simulated and analyzed using the VFSR in this paper. Results of analysis clearly indicate that this method of analysis can be further developed and used for self-diagnosis, predictive maintenance and intelligent-based monitoring

Lettuce Supply Chains and Marketing Margins in Benguet, Philippines

Understanding value chains requires knowledge of the needs of customers and how these needs are met by different suppliers of marketing or value-adding services. The need for these marketing services and costs of supplying these are reflected in marketing margins or the difference in the prices of the various marketing levels in the chain. This study analyzed lettuce supply chains in Benguet and mapped 3 chains, including the value-adding activities and the governance mechanisms such as contracts and payment terms that exist in the chain. Some new roles have emerged due to recent developments in the market. Some wholesalers became “commissioners” and “disposers,” and some individuals played dual roles along the chain. A few farmers became “disposers,” and a few “disposers” eventually became farmers. Marketing margins were also computed for a sample chain including the cost of value-adding activities to show a more accurate distribution of benefits across key actors in the chain. Higher gross margins were due to higher costs of providing marketing services, which indicates a competitive market. There are opportunities in the lettuce chains to respond to increasing demand for salad vegetables. While lettuce producers and other actors in the chain respond to these market requirements such as producing new lettuce varieties, there are issues that need to be addressed to improve efficiency and performance of the chain

Sero-Epidemiology as a Tool to Screen Populations for Exposure to Mycobacterium ulcerans

Sero-epidemiological analyses revealed that a higher proportion of sera from individuals living in the Buruli ulcer (BU) endemic Densu River Valley of Ghana contain Mycobacterium ulcerans 18 kDa small heat shock protein (shsp)-specific IgG than sera from inhabitants of the Volta Region, which was regarded so far as BU non-endemic. However, follow-up studies in the Volta Region showed that the individual with the highest anti-18 kDa shsp-specific serum IgG titer of all participants from the Volta Region had a BU lesion. Identification of more BU patients in the Volta Region by subsequent active case search demonstrated that sero-epidemiology can help identify low endemicity areas. Endemic and non-endemic communities along the Densu River Valley differed neither in sero-prevalence nor in positivity of environmental samples in PCR targeting M. ulcerans genomic and plasmid DNA sequences. A lower risk of developing M. ulcerans disease in the non-endemic communities may either be related to host factors or a lower virulence of local M. ulcerans strains

Electrochemical determination of hydroquinone using hydrophobic ionic liquid-type carbon paste electrodes

Three types of carbon paste electrodes (CPEs) with different liquid binders were fabricated, and their electrochemical behavior was characterized via a potassium hexacyanoferrate(II) probe. 1-Octyl-3-methylimidazolium hexafluorophosphate ionic liquid (IL) as a hydrophobic conductive pasting binder showed better electrochemical performance compared with the commonly employed binder. The IL-contained CPEs demonstrated excellent electroactivity for oxidation of hydroquinone. A diffusion control mechanism was confirmed and the diffusion coefficient (D) of 5.05 × 10-4 cm2 s-1 was obtained. The hydrophobic IL-CPE is promising for the determination of hydroquinone in terms of high sensitivity, easy operation, and good durability

Challenges in Whole Exome Sequencing: An Example from Hereditary Deafness

Whole exome sequencing provides unprecedented opportunities to identify causative DNA variants in rare Mendelian disorders. Finding the responsible mutation via traditional methods in families with hearing loss is difficult due to a high degree of genetic heterogeneity. In this study we combined autozygosity mapping and whole exome sequencing in a family with 3 affected children having nonsyndromic hearing loss born to consanguineous parents. Two novel missense homozygous variants, c.508C>A (p.H170N) in GIPC3 and c.1328C>T (p.T443M) in ZNF57, were identified in the same ∼6 Mb autozygous region on chromosome 19 in affected members of the family. Both variants co-segregated with the phenotype and were absent in 335 ethnicity-matched controls. Biallelic GIPC3 mutations have recently been reported to cause autosomal recessive nonsyndromic sensorineural hearing loss. Thus we conclude that the hearing loss in the family described in this report is caused by a novel missense mutation in GIPC3. Identified variant in GIPC3 had a low read depth, which was initially filtered out during the analysis leaving ZNF57 as the only potential causative gene. This study highlights some of the challenges in the analyses of whole exome data in the bid to establish the true causative variant in Mendelian disease

Median raphe region stimulation alone generates remote, but not recent fear memory traces

The median raphe region (MRR) is believed to control the fear circuitry indirectly, by influencing the encoding and retrieval of fear memories by amygdala, hippocampus and prefrontal cortex. Here we show that in addition to this established role, MRR stimulation may alone elicit the emergence of remote but not recent fear memories. We substituted electric shocks with optic stimulation of MRR in C57BL/6N male mice in an optogenetic conditioning paradigm and found that stimulations produced agitation, but not fear, during the conditioning trial. Contextual fear, reflected by freezing was not present the next day, but appeared after a 7 days incubation. The optogenetic silencing of MRR during electric shocks ameliorated conditioned fear also seven, but not one day after conditioning. The optogenetic stimulation patterns (50Hz theta burst and 20Hz) used in our tests elicited serotonin release in vitro and lead to activation primarily in the periaqueductal gray examined by c-Fos immunohistochemistry. Earlier studies demonstrated that fear can be induced acutely by stimulation of several subcortical centers, which, however, do not generate persistent fear memories. Here we show that the MRR also elicits fear, but this develops slowly over time, likely by plastic changes induced by the area and its connections. These findings assign a specific role to the MRR in fear learning. Particularly, we suggest that this area is responsible for the durable sensitization of fear circuits towards aversive contexts, and by this, it contributes to the persistence of fear memories. This suggests the existence a bottom-up control of fear circuits by the MRR, which complements the top-down control exerted by the medial prefrontal cortex