Rolling element bearing fault diagnosis using wavelet transform

This paper is focused on fault diagnosis of ball bearings having localized defects (spalls) on the various bearing components using wavelet-based feature extraction. The statistical features required for the training and testing of artificial intelligence techniques are calculated by the implementation of a wavelet based methodology developed using Minimum Shannon Entropy Criterion. Seven different base wavelets are considered for the study and Complex Morlet wavelet is selected based on minimum Shannon Entropy Criterion to extract statistical features from wavelet coefficients of raw vibration signals. In the methodology, firstly a wavelet theory based feature extraction methodology is developed that demonstrates the information of fault from the raw signals and then the potential of various artificial intelligence techniques to predict the type of defect in bearings is investigated. Three artificial intelligence techniques are used for faults classifications, out of which two are supervised machine learning techniques i.e. support vector machine, learning vector quantization and other one is an unsupervised machine learning technique i.e. self-organizing maps. The fault classification results show that the support vector machine identified the fault categories of rolling element bearing more accurately and has a better diagnosis performance as compared to the learning vector quantization and self-organizing maps.     

Lévy flight artificial bee colony algorithm

Artificial bee colony (ABC) optimisation algorithm is a relatively simple and recent population-based probabilistic approach for global optimisation. The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space. In the ABC, there is a high chance to skip the true solution due to its large step sizes. In order to balance between diversity and convergence in the ABC, a Lévy flight inspired search strategy is proposed and integrated with ABC. The proposed strategy is named as Lévy Flight ABC (LFABC) has both the local and global search capability simultaneously and can be achieved by tuning the Lévy flight parameters and thus automatically tuning the step sizes. In the LFABC, new solutions are generated around the best solution and it helps to enhance the exploitation capability of ABC. Furthermore, to improve the exploration capability, the numbers of scout bees are increased. The experiments on 20 test problems of different complexities and five real-world engineering optimisation problems show that the proposed strategy outperforms the basic ABC and recent variants of ABC, namely, Gbest-guided ABC, best-so-far ABC and modified ABC in most of the experiments.     

A new water-resistant snow index for the detection and mapping of snow cover on a global scale

An up-to-date spatio-temporal change analysis of global snow cover is essential for better understanding of climate–hydrological interactions. The normalized difference snow index (NDSI) is a widely used algorithm for the detection and estimation of snow cover. However, NDSI cannot discriminate between snow cover and water bodies without use of an external water mask. A stand-alone methodology for robust detection and mapping of global snow cover is presented by avoiding external dependency on the water mask. A new spectral index called water-resistant snow index (WSI) with the capability of exhibiting significant contrast between snow cover and other cover types, including water bodies, was developed. WSI uses the normalized difference between the value and hue obtained by transforming red, green, and blue, (RGB) colour composite images comprising red, green, and near-infrared bands into a hue, saturation, and value (HSV) colour model. The superiority of WSI over NDSI is confirmed by case studies conducted in major snow regions globally. Snow cover was mapped by considering monthly variation in snow cover and availability of satellite data at the global scale. A snow cover map for the year 2013 was produced at the global scale by applying the random walker algorithm in the WSI image supported by the reference data collected from permanent snow-covered and non-snow-covered areas. The resultant snow-cover map was compared to snow cover estimated by existing maps: MODIS Land Cover Type Product (MCD12Q1 v5.1, 2012), Global Land Cover by National Mapping Organizations (GLCNMO v2.0, 2008), and European Space Agency’s GlobCover 2009. A significant variation in snow cover as estimated by different maps was noted, and was was attributed to methodological differences rather than annual variation in snow cover. The resultant map was also validated with reference data, with 89.46% overall accuracy obtained. The WSI proposed in the research is expected to be suitable for seasonal and annual change analysis of global snow cover.     

A compact printed multistubs loaded resonator rectangular monopole antenna design for multiband wireless systems

In the present article, a compact triple‐band multistubs loaded resonator printed monopole antenna is proposed. The antenna consists of a quarter wavelength two asymmetrical inverted L‐shaped stubs to excite two resonant modes for 3.5/5.5 GHz bands and one integrated horizontally T‐shaped stub with inverted long L‐shaped stub to excite resonant mode for 2.5 GHz band. By loading these stub resonators along y‐axis with distinct gaps, the antenna resonates at three frequencies 2.57/3.52/5.51 GHz covering the desired bands while keeping compact size of 24 × 30 mm² (0.2 × 0.25 ). The proposed antenna is fabricated on Rogers RT/duroid 5880 substrate with thickness 0.79 mm and its performance experimentally verified. The measured results reveal that the antenna has the impedance bandwidths of about 210 MHz (2.50‐2.71 GHz), 260 MHz (3.37‐3.63 GHz), and 650 MHz (5.20‐5.85 GHz), for 2.5/3.5/5.5 GHz WiMAX and 5.2/5.8 GHz WLAN band systems. The antenna provides omnidirectional radiation patterns and flat antenna gains over the three operating bands. In addition, the design approach and effects of multistubs resonator lengths on the operating bands are also examined and discussed in detail.     

Tri‐band composite cylindrical dielectric resonator antenna with hybrid mode excitation and cross‐polarization suppression

This communication investigates composite cylindrical dielectric resonator antenna (CDRA) for various wireless applications. Three important features of proposed antenna design are (i) realization of two different hybrid modes, that is, HEM_11δ and HEM_12δ mode in CDRA with the help of modified annular ring printed line (work as both magnetic dipole and electric dipole), both the hybrid modes support broadside radiation characteristics (ii) suppression of HEM_21δ mode, in order to reduce the cross‐polarization level in H‐plane of other hybrid modes (HEM_11δ and HEM_12δ mode) by an amount of 8‐10 dB (iii) creation of triple‐band attribute using the concept of composite antenna. The proposed antenna design has been fabricated and practically tested. Simulated outcomes show good agreement with measured outcomes. It works in three frequency bands, that is, 2.25‐2.79 GHz, 3.1‐4.0 GHz, and 5.05‐5.6 GHz. The designed antenna structure is appropriate for WLAN and WiMAX applications.     

Reliability evaluation and optimal design in heterogeneous multi-state series-parallel systems

This paper addresses the heterogeneous redundancy allocation problem in multi-state series-parallel reliability structures with the objective to minimize the total cost of system design satisfying the given reliability constraint and the consumer load demand. The demand distribution is presented as a piecewise cumulative load curve and each subsystem is allowed to consist of parallel redundant components of not more than three types. The system uses binary capacitated components chosen from a list of available products to provide redundancy so as to increase system performance and reliability. The components are characterized by their feeding capacity, reliability and cost. A system that consists of elements with different reliability and productivity parameters has the capacity strongly dependent upon the selection of constituent components. A binomial probability based method to compute exact system reliability index is suggested. To analyze the problem and suggest an optimal/near-optimal system structure, an ant colony optimization algorithm has been presented. The solution approach consists of a series of simple steps as used in early ant colony optimization algorithms dealing with other optimization problems and offers straightforward analysis. Four multi-state system design problems have been solved for illustration. Two problems are taken from the literature and solved to compare the algorithm with the other existing methods. The other two problems are based upon randomly generated data. The results show that the method can be appealing to many researchers with regard to the time efficiency and yet without compromising over the solution quality.     

Homotopy-based surface reconstruction with application to?acoustic signals

This work introduces a new algorithm for surface reconstruction in ℝ³ from spatially arranged one-dimensional cross sections embedded in ℝ³. This is generally the case with acoustic signals that pierce an object non-destructively. Continuous deformations (homotopies) that smoothly reconstruct information between any pair of successive cross sections are derived. The zero level set of the resulting homotopy field generates the desired surface. Four types of homotopies are suggested that are well suited to generate a smooth surface. We also provide derivation of necessary higher order homotopies that can generate a C ² surface. An algorithm to generate surface from acoustic sonar signals is presented with results. Reconstruction accuracies of the homotopies are compared by means of simulations performed on basic geometric primitives.     

Hybrid Game Strategy in Fuzzy Markov-Game-Based Control

This paper proposes a novel control approach that incorporates a hybrid game strategy in Markov-game-based fuzzy control. Specifically, we aim at designing a “safe and universally consistent” controller that exhibits an ability to maintain performance against large disturbance and environment variations. The proposed hybrid control is a convex combination (based on experiential information) of “a variation of cautious fictitious play” approach and the “minimax” control approach implemented on a fuzzy Markov game platform. We show analytical convergence of Markov-game-based control in the presence of bounded external disturbances, and extend the analysis to show convergence of the proposed Markov-game-based hybrid control approach. Controller simulation and comparison against baseline Markov game fuzzy control and fuzzy $Q$ -learning control on a highly nonlinear two-link robot brings out the superiority of the approach in handling severe environment and disturbance variations over different desired trajectories. This paper illustrates the possibility of obtaining “universal consistency,” i.e., reasonable performance against severe environment and disturbance variations, by hybridizing “cautious fictitious play” with “minimax” approaches in Markov-game-based control.