•SGMD has good decomposition performance in dealing with complex signals.•SGMD, using symplectic geometry similarity transformation, can keep the essential character of the original signals ...unchanged.•The SGMD method is applied to the noisy signal to verify its robustness.•The SGMD performs better on the diagnosis of rotating machinery compound fault.
Various existed time-series decomposition methods, including wavelet transform, ensemble empirical mode decomposition (EEMD), local characteristic-scale decomposition (LCD), singular spectrum analysis (SSA), etc., have some defects for nonlinear system signal analysis. When the signal is more complex, especially noisy signal, the component signal is forced to decompose into several incomplete components by LCD and SSA. In addition, the wavelet transform and EEMD need user-defined parameters, and they are very sensitive to the parameters. Therefore, a new signal decomposition algorithm, symplectic geometry mode decomposition (SGMD), is proposed in this paper to decompose a time series into a set of independent mode components. SGMD uses the symplectic geometry similarity transformation to solve the eigenvalues of the Hamiltonian matrix and reconstruct the single component signals with its corresponding eigenvectors. Meanwhile, SGMD can efficiently reconstruct the existed modes and remove the noise without any user-defined parameters. The essence of this method is that signal decomposition is converted into symplectic geometry transformation problem, and the signal is decomposed into a set of symplectic geometry components (SGCs). The analysis results of simulation signals and experimental signals indicate that the proposed time-series decomposition approach can decompose the analyzed signals accurately and effectively.
From 1933 onward, Nazi Germany undertook massive and unprecedented industrial integration, submitting an entire economic sector to direct state oversight. This innovative study explores how German ...professionals navigated this complex landscape through the divergent careers of business managers in two of the era's most important trade organizations. While Jakob Reichert of the iron and steel industry unexpectedly resisted state control and was eventually driven to suicide, Karl Lange of the machine builders' association achieved security for himself and his industry by submitting to the Nazi regime. Both men's stories illuminate the options available to industrialists under the Third Reich, as well as the real priorities set by the industries they served.
Classificada como descritiva, de levantamento e quantitativa, esta pesquisa teve como objetivo relacionar e ranquear os atributos de valor percebido pelo cliente na escolha por máquinas agrícolas. A ...população analisada abrangeu 150 produtores rurais, indicados pelas principais empresas do ramo agrícola, e contou com o retorno de 94 respondentes, que tiveram suas propriedades classificadas em pequeno, médio e de grande porte. Neste estudo, os 5 Ps do Marketing foram analisados: Preço, Praça, Promoção, Produto e Pós-venda, no qual a análise estatística descritiva para o levantamento de informações e ambientação da amostra estudada foi realizada, bem como aplicados dois métodos quantitativos multivariados: a análise de Entropia da Informação, proposta por Zeleny (1982) e o Topsis, desenvolvido por Hwang e Yoon (1981). Constatou-se que, independentemente do tamanho, o “P” referente ao pós-venda, que compõe fatores como bom tratamento das necessidades do cliente, bons serviços prestados, qualidade na assistência técnica, elevado conhecimento técnico dos profissionais e garantias, nessa ordem, representam as principais características consideradas relevantes e que agregam valor às máquinas agrícolas. Além do pós-venda, em segundo lugar, fatores ligados ao produto, como qualidade, custo de reposição, durabilidade, confiabilidade, tecnologia, inovação e satisfação são pontos fortemente analisados. Infere-se que a perspectiva de venda de uma experiência/finalidade agrega mais valor, ou é mais considerada pelos respondentes do que uma perspectiva de produto. Essa informação é relevante e pertinente para as montadoras de maquinário agrícola para que o investimento em inovação e novas tecnologias se estenda à experiência do agricultor na pós-venda, e não somente no produto.
This paper presents a convolutional neural network (CNN) based approach for fault diagnosis of rotating machinery. The proposed approach incorporates sensor fusion by taking advantage of the CNN ...structure to achieve higher and more robust diagnosis accuracy. Both temporal and spatial information of the raw data from multiple sensors is considered during the training process of the CNN. Representative features can be extracted automatically from the raw signals. It avoids manual feature extraction or selection, which relies heavily on prior knowledge of specific machinery and fault types. The effectiveness of the developed method is evaluated by using datasets from two types of typical rotating machinery, roller bearings, and gearboxes. Compared with traditional approaches using manual feature extraction, the results show the superior diagnosis performance of the proposed method. The present approach can be extended to fault diagnosis of other machinery with various types of sensors due to its end to end feature learning capability.
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•A deep autoencoder feature learning method is proposed.•Maximum correntropy is used to design the new deep autoencoder loss function.•Artificial fish swarm algorithm is used to ...optimize parameters.
The operation conditions of the rotating machinery are always complex and variable, which makes it difficult to automatically and effectively capture the useful fault features from the measured vibration signals, and it is a great challenge for rotating machinery fault diagnosis. In this paper, a novel deep autoencoder feature learning method is developed to diagnose rotating machinery fault. Firstly, the maximum correntropy is adopted to design the new deep autoencoder loss function for the enhancement of feature learning from the measured vibration signals. Secondly, artificial fish swarm algorithm is used to optimize the key parameters of the deep autoencoder to adapt to the signal features. The proposed method is applied to the fault diagnosis of gearbox and electrical locomotive roller bearing. The results confirm that the proposed method is more effective and robust than other methods.
The endosomal sorting complex required for transport (ESCRT) machinery is an ancient system that deforms membrane and severs membrane necks from the inside. Extensive evidence has accumulated to ...demonstrate the conserved functions of plant ESCRTs in multivesicular body (MVB) biogenesis and MVB-mediated membrane protein sorting. In addition, recent exciting findings have uncovered unique plant ESCRT components and point to emerging roles for plant ESCRTs in non-endosomal sorting events such as autophagy, cytokinesis, and viral replication. Plant-specific processes, such as abscisic acid (ABA) signaling and chloroplast turnover, provide further evidence for divergences in the functions of plant ESCRTs during evolution. We summarize the multiple roles and current working models for plant ESCRT machinery and speculate on future ESCRT studies in the plant field.
ESCRT is an evolutionarily conserved machinery for membrane deformation and scission from the inner face of a membrane away from the cytoplasm.
Plants encode most ESCRT isoforms in their genome, including ESCRT-I, -II, -III, and VPS4/SKD1, with the exception of the canonical ESCRT-0. TOL (TOM1-like) proteins were identified as upstream ESCRT factors that partially fulfill ESCRT-0 function in plants.
Extensive evidence has accumulated to demonstrate the essential and conserved functions of ESCRTs in endosomal sorting in plants.
Plant-specific ESCRT components have been identified. In addition, ESCRTs in plants are also involved in a variety of non-endosomal sorting events such as autophagosome maturation, chloroplast turnover, cytokinesis, and viral replication.
Plant ESCRTs are also actively involved in hormone signaling and plant responses to biotic and abiotic stresses.
The roller is an important part of the belt conveyor used in coal transportation. Due to the harsh environment of coal mines, the rollers are in a state of high load and high friction for a long ...time, which causes wear failure and has a serious impact on the reliability and safety of the equipment. In order to prepare roller material with excellent bearing performance and friction performance, CF/PUE composites were prepared by pouring method with polyurethane as the matrix and carbon fiber as reinforcement. Due to the low surface activity of unmodified carbon fibers and poor bonding performance with the matrix, MoSsub.2 was generated on the surface of carbon fiber by the in situ generation method in this paper. It was found that the mechanical properties of MoSsub.2/CF/PUE composites were better when the CF content was 0.3 wt%. The Shore hardness reached 92.2 HA, which is 10% higher than pure polyurethane. The tensile strength was 38.44 MPa, which is 53% higher than pure polyurethane. The elongation at break was 850%, which is 16% higher than pure polyurethane. The maximum compressive stress was 2.32 MPa, which is 42% higher than pure polyurethane. The friction coefficient was much lower than that of pure PUE composites, the friction coefficient was 0.284, which is 59% lower than pure polyurethane.
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