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Mycenae paranaenses
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ISBN: 0444858172 9780444858177 Year: 1997 Volume: 97 Publisher: Amsterdam : North-Holland,

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Book
Deep Learning-Based Machinery Fault Diagnostics
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ISBN: 3036551743 3036551735 Year: 2022 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

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This book offers a compilation for experts, scholars, and researchers to present the most recent advancements, from theoretical methods to the applications of sophisticated fault diagnosis techniques. The deep learning methods for analyzing and testing complex mechanical systems are of particular interest. Special attention is given to the representation and analysis of system information, operating condition monitoring, the establishment of technical standards, and scientific support of machinery fault diagnosis.

Keywords

Technology: general issues --- History of engineering & technology --- process monitoring --- dynamics --- variable time lag --- dynamic autoregressive latent variables model --- sintering process --- hammerstein output-error systems --- auxiliary model --- multi-innovation identification theory --- fractional-order calculus theory --- canonical variate analysis --- disturbance detection --- power transmission system --- k-nearest neighbor analysis --- statistical local analysis --- intelligent fault diagnosis --- stacked pruning sparse denoising autoencoder --- convolutional neural network --- anti-noise --- flywheel fault diagnosis --- belief rule base --- fuzzy fault tree analysis --- Bayesian network --- evidential reasoning --- aluminum reduction process --- alumina concentration --- subspace identification --- distributed predictive control --- spatiotemporal feature fusion --- gated recurrent unit --- attention mechanism --- fault diagnosis --- evidential reasoning rule --- system modelling --- information transformation --- parameter optimization --- event-triggered control --- interval type-2 Takagi–Sugeno fuzzy model --- nonlinear networked systems --- filter --- gearbox fault diagnosis --- convolution fusion --- state identification --- PSO --- wavelet mutation --- LSSVM --- data-driven --- operational optimization --- case-based reasoning --- local outlier factor --- abnormal case removal --- bearing fault detection --- deep residual network --- data augmentation --- canonical correlation analysis --- just-in-time learning --- fault detection --- high-speed trains --- autonomous underwater vehicle --- thruster fault diagnostics --- fault tolerant control --- robust optimization --- ocean currents --- n/a --- interval type-2 Takagi-Sugeno fuzzy model


Book
Mining Safety and Sustainability I
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ISBN: 303654688X 3036546871 Year: 2022 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

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Safety and sustainability are becoming ever bigger challenges for the mining industry with the increasing depth of mining. It is of great significance to reduce the disaster risk of mining accidents, enhance the safety of mining operations, and improve the efficiency and sustainability of development of mineral resource. This book provides a platform to present new research and recent advances in the safety and sustainability of mining. More specifically, Mining Safety and Sustainability presents recent theoretical and experimental studies with a focus on safety mining, green mining, intelligent mining and mines, sustainable development, risk management of mines, ecological restoration of mines, mining methods and technologies, and damage monitoring and prediction. It will be further helpful to provide theoretical support and technical support for guiding the normative, green, safe, and sustainable development of the mining industry.

Keywords

Technology: general issues --- History of engineering & technology --- top-coal caving mining --- process parameters --- decision model --- BP neural network --- similaritysimulation test --- time-dependent cohesion --- traction force --- deep-sea sediment --- tracked miner --- rheology --- cemented paste backfill --- curing conditions --- mechanical properties --- mathematical strength model --- AMD --- phytoremediation --- sulfate --- hydroponic experiment --- wetland plants --- ecological pollution --- tailings dam --- safety factor --- quantitative evaluation --- dynamic weight --- comprehensivediagnosis of health --- : rock formations --- surface subsidence law --- surface subsidence process --- 3D test device --- 3Dlaser scanning --- mine ventilation network --- wind speed sensors distribution --- air volume reconstruction --- independent cut set --- surface subsidence --- probability integration --- loess donga --- superimposed calculation --- additional displacement of slope mining slip --- : mining water hazard --- microseismic monitoring --- intelligent recognition --- feature extraction --- support vector machine --- classification model --- freeze–thaw cycles --- tailings --- mechanical behavior --- SEM --- MIP --- thick aeolian sand --- shallow buried thick seam --- overburden failure --- ground damage --- numerical simulation --- rock mechanics --- cyclic impact --- chemical corrosion --- axial compression --- strength degradation --- pipe transportation system test --- pressure loss --- random forest algorithm --- filling-aided design --- vibration signals --- neural network --- drilling state identification algorithm --- drilling depth --- monitoring-while-drilling method ---  

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