Classification of faults in mechanical components using machine learning is a hot topic in the field of science and engineering. Generally, every real-world running mechanical system exhibits ...personalized vibration behaviors that can be measured with acceleration sensors. However, faulty samples of such systems are difficult to obtain. Therefore, machine learning methods, such as support vector machine (SVM), neural network (NNs), etc., fail to obtain agreeable fault detection results through smart sensors. A personalized diagnosis fault method is proposed to activate the smart sensor networks using finite element method (FEM) simulations. The method includes three steps. Firstly, the cosine similarity updated FEM models with faults are constructed to obtain simulation signals (fault samples). Secondly, every simulation signal is separated into sub-signals to solve the time-domain indexes to generate the faulty training samples. Finally, the measured signals of unknown samples (testing samples) are inserted into the trained SVM to classify faults. The personalized diagnosis method is applied to detect bearing faults of a public bearing dataset. The classification accuracy ratios of six types of faults are 90% and 92.5%, 87.5% and 87.5%, 85%, and 82.5%, respectively. It confirms that the present personalized diagnosis method is effectiveness to detect faults in the absence of fault samples.
Since the desire for real-time human health monitoring as well as seamless human-machine interaction is increasing rapidly, plenty of research efforts have been made to investigate wearable sensors ...and implantable devices in recent years. As a novel 2D material, graphene has aroused a boom in the field of sensor research around the world due to its advantages in mechanical, thermal, and electrical properties. Numerous graphene-based sensors used for human health monitoring have been reported, including wearable sensors, as well as implantable devices, which can realize the real-time measurement of body temperature, heart rate, pulse oxygenation, respiration rate, blood pressure, blood glucose, electrocardiogram signal, electromyogram signal, and electroencephalograph signal, etc. Herein, as a review of the latest graphene-based sensors for health monitoring, their novel structures, sensing mechanisms, technological innovations, components for sensor systems and potential challenges will be discussed and outlined.
Direct asymmetric reductive amination is one of the most efficient methods for the construction of chiral amines, in which the scope of the applicable amine coupling partners remains a significant ...challenge. In this study we describe primary alkyl amines effectively serve as the N-sources in direct asymmetric reductive amination catalyzed by the iridium precursor and sterically tunable chiral phosphoramidite ligands. The density functional theory studies of the reaction mechanism imply the alkyl amine substrates serve as a ligand of iridium strengthened by a (N)H-O(P) hydrogen-bonding attraction, and the hydride addition occurs via an outer-sphere transition state, in which the Cl-H H-bonding plays an important role. Through this concise procedure, cinacalcet, tecalcet, fendiline and many other related chiral amines have been synthesized in one single step with high yields and excellent enantioselectivity.
The highly efficient direct catalytic reductive amination of ketones with diphenylmethanamine catalyzed by iridium–phosphoramidite complexes is described. As an effective coupling partner, ...diphenylmethanamine is suitable for a wide range of ketones to provide chiral amines in high yields and enantioselectivity. The chiral monodentate phosphoramidite ligands are tunable and competent to accommodate substrates with different structures.
Case 1.
The scheme of the APSM enhanced cepstrum analysis to detect faults under constant speed condition.
Case 2.
The scheme of the APSM enhanced cepstrum analysis to detect faults under variable ...speed conditions.
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•Asymmetric penalty sparse model (APSM) enhanced cepstrum analysis is proposed for fault detection.•APSM and cepstrum analysis are applied to purify vibration signals and effectiveness extract periodic impulses, respectively.•The superiority is verified by numerical and experiment investigations both in stationary and non-stationary conditions.•For non-stationary condition, multi-synchrosqueezing transform (MSST) is employed for non-stationary conditions to estimate the instantaneous frequency (IF) to achieve the tacholess measurement.
Signal processing approaches of rotating machine are well-established and wildly used in machine condition monitoring. Cepstrum analysis has the ability to transform related components from convolution form to addition form and suitable for the extraction of the periodic impulse components. However, the fault features are often localized in heavy background noises caused by the operation condition, which limit the application of cepstrum analysis. In this paper, a method is proposed by introducing the asymmetric penalty sparse model (APSM) to improve the effectiveness of cepstrum. The core idea of APSM is a sparse optimization formulation solved by the alternating direction method to achieve sparse feature extraction without any prior knowledge. The detection of bearing faults both in stationary and non-stationary conditions are given by using simulation and experimental signals. The performance of the proposed method is verified and the superiority is addressed by comparing with cesptrum analysis.
Asymmetric hydrogenation (AH) and direct reductive amination (DRA) are both efficient transformations frequently utilized in industry. Here we combine the asymmetric hydrogenation of prochiral ...olefins and direct reductive amination of aldehydes in one step using hydrogen gas as the common reductant and a rhodium-Segphos complex as the catalyst. With this strategy, the efficiency for the synthesis of the corresponding chiral amino compounds is significantly improved. The practical application of this synthetic approach is demonstrated by the facile synthesis of chiral 3-phenyltetrahydroquinoline and 3-benzylindoline compounds.
Understanding the changing role of central banks and their recent novel policies is essential for analysing many economic and financial issues, ranging from financial regulation and crisis, to ...exchange rate dynamics and regime changes, and QE and prolonged low interest rates. This book features contributions by the world's leading experts on central banking, providing in accessible essays a fascinating review of today's key issues for central banks. Luminaries including Stephen Cecchetti, Takatoshi Ito, Anil Kashyap, Mervyn King, Donald Kohn, Otmar Issing and Hyun Shin are joined by Charles Goodhart of the London School of Economics and Political Science, whose many achievements in the field of central banking are honoured as the inspiration for this book. The Changing Fortunes of Central Banking discusses the developing role of central banks in seeking monetary and financial stabilisation, while also giving suggestions for model strategies. This comprehensive review will appeal to central bankers, financial supervisors and academics.
Brain–machine interface (BMI) is a device that translates neuronal information into commands, which is capable of controlling external software or hardware, such as a computer or robotic arm. In ...consequence, the electrodes with desirable electrical and mechanical properties for direct interacting between neural tissues and machines serves as the crucial and critical part of BMI technology. Nowadays, the development of material science provides many advanced electrodes for neural stimulating and recording. Particularly, the widespread applications of nanotechnologies have innovatively introduced biocompatible electrode that can have similar characteristics with neural tissue. This paper reviews the existing problems and discusses the latest development of electrode materials for BMI, including conducting polymers, silicon, carbon nanowires, graphene, and hybrid organic–inorganic nanomaterials. In addition, we will inspect at the technical and scientific challenges in the development of neural electrode for a broad application of BMI with focus on the biocompatibility, mechanical mismatch, and electrical performance of electrode materials.
Designing neural electrodes with both appropriate electrical and mechanical properties becomes more and more important in the field of brain–machine interfaces. Recently, investigating in material science to innovate biocompatible nanomaterials is of great significance.
Conventional signal processing techniques for fault detection are usually aimed at constant speed conditions. Nowadays, order tracking, especially tacho‐less order tracking is regarded as a valuable ...tool for extracting fault features under variable rotational speed conditions. Therefore, a teager energy operator (TEO)‐based modified Laplacian of Gaussian filter is proposed to enhance the fault detection behaviour of tacho‐less order tracking. This method consists of four steps: First, multi‐synchrosqueezing transform is employed to estimate and then extract the instantaneous rotation frequency of a shaft. Second, based on the extracted curve, the non‐stationary domain signal is converted into a quasi‐stationary domain by the re‐sampling technique. Third, the obtained quasi‐stationary domain signal is de‐noise by the novel method. Finally, fault characteristic orders are extracted via envelope order spectrum analysis method and the performance is significantly improved. The results of numerical simulation and experimental investigations are performed to validate the superiority of the novel method for fault extraction under variable rotational speed conditions.
In this article we demonstrate how asymmetric total synthesis of (
)-rivastigmine has been achieved using direct asymmetric reductive amination as the key transformation in four steps. The route ...started with readily available and cheap
-hydroxyacetophenone, through esterification, asymmetric reductive amination,
-diphenylmethyl deprotection and reductive amination, to provide the final (
)-rivastigmine in 82% overall yield and 96% enantioselectivity. In the asymmetric reductive amination, catalysed by the iridium⁻phosphoramidite ligand complex and helped by some additives, the readily prepared 3-acetylphenyl ethyl(methyl)carbamate directly reductively coupled with diphenylmethanamine to yield the chiral amine product in 96%
and 93% yield.
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