Prognosis of Bearing Acoustic Emission Signals Using Supervised Machine Learning

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Acoustic emission (AE) technique can be successfully utilized for condition monitoring of various machining and industrial processes. To keep machines function at optimal levels, fault prognosis model to predict the remaining useful life (RUL) of machine components is required. This model is used to analyze the output signals of a machine whilst in operation and accordingly helps to set an early alarm tool that reduces the untimely replacement of components and the wasteful machine downtime. Recent improvements indicate the drive on the way towards incorporation of prognosis and diagnosis machine learning techniques in future machine health management systems. With this in mind, this work employs three supervised machine learning techniques; support vector machine regression, multilayer artificial neural network model and gaussian process regression, to correlate AE features with corresponding natural wear of slow speed bearings throughout series of laboratory experiments. Analysis of signal parameters such as signal intensity estimator and root mean square was undertaken to discriminate individual types of early damage. It was concluded that neural networks model with back propagation learning algorithm has an advantage over the other models in estimating the RUL for slow speed bearings if the proper network structure is chosen and sufficient data is provided.Peer reviewe

Blind Two-Dimensional Super-Resolution and Its Performance Guarantee

In this work, we study the problem of identifying the parameters of a linear system from its response to multiple unknown input waveforms. We assume that the system response, which is the only given information, is a scaled superposition of time-delayed and frequency-shifted versions of the unknown waveforms. Such kind of problem is severely ill-posed and does not yield a unique solution without introducing further constraints. To fully characterize the linear system, we assume that the unknown waveforms lie in a common known low-dimensional subspace that satisfies certain randomness and concentration properties. Then, we develop a blind two-dimensional (2D) super-resolution framework that applies to a large number of applications such as radar imaging, image restoration, and indoor source localization. In this framework, we show that under a minimum separation condition between the time-frequency shifts, all the unknowns that characterize the linear system can be recovered precisely and with very high probability provided that a lower bound on the total number of the observed samples is satisfied. The proposed framework is based on 2D atomic norm minimization problem which is shown to be reformulated and solved efficiently via semidefinite programming. Simulation results that confirm the theoretical findings of the paper are provided

Unemployment and Labor Market Institutions: Theory and Evidence from the GCC

The theoretical model delves into the relationship between labor market institutions and unemployment by proving two propositions: (1) allowing informal activity bolsters job creation, and (2) if the institutional environment is initially, sufficiently, weak, then mitigating it will lower unemployment. Simulating the model with the GCC’s unemployment for the period 1990-2007 allows us to decipher the validity of the model. The institutional environment is represented in this simulation by social insurance which is captured through oil prices. Hence, an increase in oil prices is assumed to lead to higher social insurance and, therefore ,to higher cost of hiring labour . The parameters are selected with the objective of minimizing the error gap between the effective unemployment rate and the simulated unemployment rate . The effective unemployment rate is constructed as a weighted average of the unemployment rate of nationals and non-nationals. The weights are the shares of national and non-national labour-force in the GCC countries. Expositional simulations verified the second proposition. Thus, improving labor market institutions, that are initially weak may discernibly alleviate unemployment problems in the GCC.Unemployment; institutions; GCC

The Institutional Environment and the Banking - Growth Nexus: Theory and Investigation for MENA

This paper seeks to provide some theoretical and empirical answers to the following question: Does the institutional environment affect the causality relationship between banking development and economic growth? In the theoretical part, we develop an endogenous growth model where the institutional environment is captured through two indicators: the judicial system efficiency and the easiness of informal trade. We show that an improvement of the institutional environment has two effects. First, it intensifies the causality direction from banking to economic growth through a reduction of defaulting loans. Second, it reduces the interest rate spread. In the empirical part, considering twenty-two MENA countries over the period 1984-2004, we find a bi-directional causality. The first one, which runs from banking development to economic growth, is more intense in countries with a more developed institutional environment. The second causality runs from economic growth to banking and indicates that a more developed economy has a more developed banking system.Banking; Growth; Institutions; MENA

The effect of the seasonal cerebro-spinal meningitis on the incidence of hydrocephalus in Sudanese children

The inflammatory process of meningitis may obstruct the circulation of cerebrospinal fluid culminating into increased intracranial tension and in children before closure of their frontanel may lead to hydrocephalus. This study was constructed to find out the impact of the out break of meningococcal meningitis into the frequency of hydrocephalus in young children. We found that the peak of the incidence of acquired hydrocephalus in young children follows that of the seasonal cerebro-spinal meningitis (CSM) by few weeks. The age group affected by post-meningetic hydrocephalus was that below two years. Children of this age group were not included in the national vaccination program against cerebro-spinal meningitis at the time of the study, which may be the cause of their high susceptibility. Keywords: hydrocephalus, meningococcal meningitis Sudan Journal of Medical Sciences Vol. 1(1) 2006: 41-4

Snail abundance in freshwater canals in the eastern province of Saudi Arabia and acute toxicity studies of copper sulphate in Biomphalaria arabica and Lymnaea auricularia

The present study aimed to investigate the distribution of three species of freshwater snails, namely; Biomphalaria Arabica; Planorbidae, Lymnaea auricularia; Lymnaeidae and Melanoides tuberculatus; Thiaridae in two different parallel canals (the concrete irrigation and the earthen drainage canals) in the eastern province of Saudi Arabia and the effect of copper sulphate pentahydrate (CuSO4.5H2O) on mortality of the first two species after 24 h of exposure. The physico-chemical properties of the water especially, temperature and pH were determined as important factors for snail distribution. The results show that the water temperature and the pH of the two canals were almost the same. The range of water temperature was 25.8 to 28.3°C, while the water pH was 6.6 to 6.8. The two canals were occupied by three species of aquatic snails viz. B. arabica, L. auricularia and M. tuberculatus. The bioassay of CuSO4.5H2O on only two snail species showed 24 h–LC50 as 5.7 ppm for B. arabicus and 7.8 ppm for L. auricularia. This result reveals that CuSO4.5H2O was highly effective in snail eradication. On the basis of the present study, it is recommended that some further studies on the canals including all environmental factors should be investigated for their role in aquatic snail distribution. However, the chronic effect of lower lethal dose of CuSO4.5H2O on the snails mortality and their effects on developmental stages should be investigated, and some local plant extract should also be tried for their potency on snail mortality.Key words: Biomphalaria, Lymnea, Melanoides, distribution, freshwater snails, copper sulphate, Saudi Arabia

Impact of English Orthography on Learning English Sounds and Spelling

In order to learn or study English as a foreign language, the learner must be aware of pronunciation skills besides other skills which are of great importance for studying it. In Sudan, there is a large number of people who are interested in learning English as a foreign language. Among them are the students of English language at the University of Gezira. Many studies have demonstrated that the errors made by the speakers of other language who speak English, are systematic rather than random. For instance, scholars and linguists demonstrated that Arab learners of English face problems in pronunciation of sound which they are not familiar with. The present study is limited to the University of Gezira, Faculty of Education – Hassahisa English Department, students during the academic year 2015-2016 and the teachers who teach at University of Gezira-Faculty of Education Hantoub-English Department. The researcher followed the analytical descriptive method to carry out the study. The tools used by the researcher were i) a test for students of 3rd Semester at the University of Gezira, Faculty of Education, Hassahiesa ii) a questionnaire for teachers at University of Gezira, Faculty of Education-Hantoub. Correct pronunciation and spelling have been always a great challenge for the EFL learners. The present research is at attempt to find that how English orthography affects the learning of English sounds and spelling. Moreover, the research may benefit syllabus designers as well as English students who are specialized in the field of English Language by providing lights and hints in the scope of how to write in correct spelling. Keywords: orthography, pronunciation, EFL, University of Gezira, descriptive metho

An FPGA Test bed for Spectrum Sensing in Cognitive Radio

In this thesis we presented a research test bed for spectrum sensing in cognitive radio systems. We considered spectrum sensing based on Eigen values of sample covariance matrix. When considering the implementation of the algorithm , it will pose a question on how to generate the Eigen values with low complexity. In practice, there is a trade-off between complexity and detection performance. The Eigen values of the sample covariance matrix can be found by using a Discrete Fourier Transform (DFT) , which can be implemented in hardware using Fats Fourier Transform (FFT). Simulations are performed in MATLAB and real-time measurements carried out in Xilinx Kintex-7 Field Programmable Gate Array (FPGA). The result shows that the probability of detection increased as Signal to Noise Ratio (SNR) increases. For Hardware result it shows less performance because the threshold is being calculated theoretically and the processing delay of FFT causes the distribution under hypothesis 1 (signal + noise) to be delayed from the distribution under hypothesis 0 (noise only).In terms of the computational complexity, the Eigen values method which proposed in [6], is about M times that of the Number of samples Ns , where M is the autocorrelation length of the received signal. However our proposed method only needs 2*M LUT(Look Up Tables) as shown in table 3. The simulations and implementation show that the proposed method works well with low complexity, without using information of the signal, the channel and noise power compared to the current spectrum sensing state of the art. we present a feasibility study of spectrum sensing using a research test bed platform for exploration and demonstration of development of physical layer functionalities for cognitive radio systems. Keywords: Cognitive Radio, spectrum sensing, Eigen values, FPG