To assess health conditions of rotating machinery efficiently, multiple accelerometers are mounted on different locations to acquire a variety of possible faults signals. The statistical features are extracted from these signals to identify the running status of a machine. However, the acquired vibration signals are different due to sensor’s arrangement and environmental interference, which may lead to different diagnostic results. In order to improve the fault diagnosis reliability, a new multisensor data fusion technique is proposed. First, time-domain and frequency-domain features are extracted from the different sensor signals, and then these features are input into multiple two-layer sparse autoencoder (SAE) neural networks for feature fusion. Finally, fused feature vectors can be regarded as the machine health indicators, and be used to train deep belief network (DBN) for further classification. To verify the effectiveness of the proposed SAE-DBN scheme, the bearing fault experiments were conducted on a bearing test platform, and the vibration data sets under different running speeds were collected for algorithm validation. For comparison, different feature fusion methods were also applied to multisensor fusion in the experiments. Experimental results demonstrated that the proposed approach can effectively identify the machine running conditions and significantly outperform other fusion methods.

Multisensor Feature Fusion for Bearing Fault Diagnosis Using Sparse Autoencoder and Deep Belief Network

Owing to their capability of bypassing conventional high-priced and inflexible silicon based electronics to manufacture a variety of devices on flexible substrates by using large-scale and high-volume printing techniques, printed electronics (PE) have attracted increasing attention in the field of manufacturing industry for electronic devices This simple and cost-effective approach could enhance current methods of constructing a patterned surface for nanomaterials and offer opportunities for developing fully-printed functional devices, especially offering the possibility of ubiquitous low-cost and flexible devices This review presents a summary of work to date on the inorganic nanomaterials involved in PE applications, focused on the utilization of inorganic nanomaterials-based inks in the successful preparation of printed conductive patterns, electrodes, sensors, thin film transistors (TFTs) and other micro-/nanoscale devices The printing techniques, sintering methods and printability of functional inks with their associated challenges are discussed, and we look forward so you can glimpse the future of PE applications

Inorganic nanomaterials for printed electronics: a review

Challenges and issues facing lithium metal for solid-state rechargeable batteries

Epoxy nanocomposites reinforced with polypyrrole functionalized nano-magnetite (Fe3O4–PPy) showed significantly enhanced electromagnetic wave absorption performance and flame retardancy. The Fe3O4–PPy nanocomposites were prepared by the surface initiated polymerization method. The epoxy/(30.0 wt%)Fe3O4–PPy nanocomposites possess a minimum reflection loss (RL) value of −35.7 dB, which is much lower than that of either epoxy/(7.5 wt%)PPy nanocomposites with a minimum RL value of −11.0 dB or epoxy/(30.0 wt%)Fe3O4 with a minimum RL value of −17.8 dB at the same thickness (1.7 mm). Meanwhile, the bandwidth of epoxy/(30.0 wt%)Fe3O4–PPy nanocomposites for RL < −10 dB and RL < −20 dB is 4.0 GHz and 0.8 GHz, respectively. The increased interface area, eddy current loss and anisotropic energy are essentially important to achieve higher reflection loss and broader absorption bandwidth for epoxy/(30.0 wt%)Fe3O4–PPy nanocomposites. Moreover, the significantly reduced flammability was observed in the epoxy/(30.0 wt%)Fe3O4–PPy nanocomposites compared with pure epoxy. The total heat release of epoxy/(30.0 wt%)Fe3O4–PPy nanocomposites decreased from 25.5 kJ g−1 of pure epoxy to just 12.3 kJ g−1. The tensile strength of the epoxy nanocomposites was reported as well. These new nanocomposites with an enhanced electromagnetic wave absorption property and flame retardancy possess great potential for safer electromagnetic wave absorbers in the electronic industry to satisfy stringent industrial standards.

Polypyrrole-interface-functionalized nano-magnetite epoxy nanocomposites as electromagnetic wave absorbers with enhanced flame retardancy

School of Materials Science and Engineering, North University of China, No. 3 Xueyuan Road, Taiyuan, Shanxi 030051, PR China College of Chemical and Environmental Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, China 3 Integrated Composites Laboratory, Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, Tennessee 37996, USA Department of Chemistry, Xavier University of Louisiana, New Orleans, Louisiana 70125, USA Department of Physics and Engineering, Frostburg State University, Frostburg, Maryland 21532, USA

Flame-retardant rigid polyurethane foam with a phosphorus-nitrogen single intumescent flame retardant

Multi-LeapMotion sensor based demonstration for robotic refine tabletop object manipulation task

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Multi-LeapMotion sensor based demonstration for robotic refine tabletop object manipulation task