In this paper, a new Multi-Layer Perceptron Neural Network (MLP NN) classifier is proposed for classifying sonar targets and non-targets from the acoustic backscattered signals. Besides the capabilities of MLP NNs, it uses Back Propagation (BP) and Gradient Descent (GD) for training; therefore, MLP NNs face with not only impertinent classification accuracy but also getting stuck in local minima as well as lowconvergence speed. To lift defections, this study uses Adaptive Best Mass Gravitational Search Algorithm (ABGSA) to train MLP NN. This algorithm develops marginal disadvantage of the GSA using the bestcollected masses within iterations and expediting exploitation phase. To test the proposed classifier, this algorithm along with the GSA, GD, GA, PSO and compound method (PSOGSA) via three datasets in various dimensions will be assessed. Assessed metrics include convergence speed, fail probability in local minimum and classification accuracy. Finally, as a practical application assumed network classifies sonar dataset. This dataset consists of the backscattered echoes from six different objects: four targets and two non-targets. Results indicate that the new classifier proposes better output in terms of aforementioned criteria than whole proposed benchmarks.
In the extra-thick coal seams and multi-layered hard roofs, the longwall hydraulic support yielding, coal face spalling, strong deformations of goaf-side entry, and severe ground pressure dynamic events typically occur at the longwall top coal caving longwall faces. Based on the Key strata theory an overburden caving model is proposed here to predict the multilayered hard strata behaviour. The proposed model together with the measured stress changes in coal seam and underground observations in Tongxin coal mine provides a new idea to analyse stress changes in coal and help to minimise rock bursts in the multi-layered hard rock ground. Using the proposed primary Key and the sub-Key strata units the model predicts the formation and instability of the overlying strata that leads to abrupt dynamic changes to the surrounding rock stress. The data obtained from the vertical stress monitoring in the 38 m wide coal pillar located adjacent to the longwall face indicates that the Key strata layers have a significant influence on ground behaviour. Sudden dynamically driven unloading of strata was caused by the first caving of the sub-Key strata while reloading of the vertical stress occurred when the goaf overhang of the sub-Key strata failed. Based on this findings several measures were recommended to minimise the undesirable dynamic occurrences including pre-split of the hard Key strata by blasting and using the energy consumption yielding reinforcement to support the damage prone gate road areas. Use of the numerical modelling simulations was suggested to improve the key theory accuracy.
Research on acoustical hoods used in industry has been widely discussed; however, the assessment of shape optimization on space-constrained close-fitting acoustic hoods by adjusting design parameters has been neglected. Moreover, the acoustical performance for a one-layer acoustic hood used in a high intensity environment seems to be insufficient. Therefore, an assessment of an optimally shaped acoustical hood with two layers will be proposed. In this paper, a numerical case for depressing the noise level of a piece of equipment by optimally designing a shaped two-layer close-fitting acoustic hood under a constrained space will be introduced. Furthermore, to optimally search for a better designed set for the multi-layer acoustical hood, an artificial immune method (AIM) has been adopted as well. Consequently, this paper provides a quick and effective method to reduce equipment noise by optimally designing a shaped multi-layer close-fitting acoustic hood via the AIM searching technique.
This study stacked a thin, dense BCuP-5 (Cu-Ag-P based filler metal) on a Cu-plate using the laser cladding (L.C) process to develop a method to manufacture Ag reducing multilayer clad electrical contact material with an Ag-M(O)/Ag/Cu/BCuP-5 structure. Then, the microstructure and macroscopic properties of the manufactured BCuP-5 coating layer were analyzed. The thickness of the manufactured coating layer was approximately 1.7 mm (maximum). Microstructural observation of the coating layer identified Cu, Ag and Cu-Ag-Cu3P ternary eutectic phases like those in the initial BcuP-5 powder. To evaluate the properties of the manufactured coating layer, hardness and adhesion strength tests were performed. The average hardness of the laser cladded coating layer was 183.2 Hv, which is 2.6 times greater than conventional brazed BcuP-5. The average pull-off strength measured using the stud pull test was 341.6 kg/cm2. Cross-sectional observation of the pulled-off material confirmed that the coating layer and substrate maintained a firm adhesion after pull-off. Thus, the actual adhesion strength of Cu/BcuP-5 was inferred to be greater than 341.6 kg/cm2. Based on the above findings, it was confirmed that it is possible to manufacture a sound Ag reducing multilayer clad electrical contact material using the laser cladding process.