The manufacturing value chain of power generation equipment: A case study

On the basis of literature study and data collection, this thesis analyzes the value chain in Chinese power industry, power generation equipment industry, and steam turbine manufacturing industry systematically, in combination with Chinese power generation equipment industry background. It obtains a conclusion that the manufacturing takes the core status in the whole value chain. Around the manufacturing value chain, this thesis analyzes the key links and the key components of manufacturing value chain by case study of Dongfang Turbine Co., Ltd. It also makes a concrete description of manufacturing value chain’s management and upgrading in the aspects of technology innovation, manufacturing technology layout optimization, production and quality management, and the management of value network.Com base na revisão de literatura e na recolha e tratamento de dados, esta tese analisa a cadeia de valor na indústria energética Chinesa no que respeita à produção de equipamento para a geração de energia e turbinas a vapor. A tese conclui que a produção assume um lugar central em toda a cadeia de valor. Tendo como pano de fundo a cadeia de valor da produção esta tese analisa as principais ligações e as principais componentes da produção da empresa Dongfang Turbine. Ltd. A tese descreve também a gestão da cadeia de valor da produção, dando especial ênfase à inovação tecnológica, à optimização do layout, à gestão da qualidade e à gestão do valor produzido em rede

Completely Precontinuous Posets

AbstractIn this paper, concepts of strongly way below relations, completely precontinuous posets, coprimes and Heyting posets are introduced. The main results are: (1) The strongly way below relations of completely precontinuous posets have the interpolation property; (2) A poset P is a completely precontinuous poset iff its normal completion is a completely distributive lattice; (3) An ω-chain complete P is completely precontinuous iff P and Pop are precontinuous and its normal completion is distributive iff P is precontinuous and has enough coprimes; (4) A poset P is completely precontinuous iff the strongly way below relation is the smallest approximating auxiliary relation on P iff P is a Heyting poset and there is a smallest approximating auxiliary relation on P. Finally, given a poset P and an auxiliary relation on P, we characterize those join-dense subsets of P whose strongly way-below relation agrees with the given auxiliary relation

Microstructure and Magnetic Properties of NdFeB Films through Nd Surface Diffusion Process

Ta/Nd/NdFeB/Nd/Ta films were deposited by magnetron sputtering on Si (100) substrates and subsequently annealed for 30 min at 923 K in vacuum. It was found that the microstructure and magnetic properties of Ta/Nd/NdFeB/Nd/Ta films strongly depend on the NdFeB layer thickness. With NdFeB layer thickness increasing, both the grain size and the strain firstly reduce and then increase. When NdFeB layer thickness is 750 nm, the strain reaches the minimum value. Meanwhile, both the in-plane and perpendicular coercivities firstly drastically increase and then slowly decrease with NdFeB layer thickness increasing. The highest in-plane and perpendicular coercivities can be obtained at NdFeB layer thickness of 750 nm, which are 21.2 kOe and 19.5 kOe, respectively. In addition, the high remanence ratio (remanent magnetization/saturation magnetization) of 0.87 can also be achieved in Ta/Nd/NdFeB (750 nm)/Nd/Ta film

Self-adjustable domain adaptation in personalized ECG monitoring integrated with IR-UWB radar

To enhance electrocardiogram (ECG) monitoring systems in personalized detections, deep neural networks (DNNs) are applied to overcome individual differences by periodical retraining. As introduced previously [4], DNNs relieve individual differences by fusing ECG with impulse radio ultra-wide band (IR-UWB) radar. However, such DNN-based ECG monitoring system tends to overfit into personal small datasets and is difficult to generalize to newly collected unlabeled data. This paper proposes a self-adjustable domain adaptation (SADA) strategy to prevent from overfitting and exploit unlabeled data. Firstly, this paper enlarges the database of ECG and radar data with actual records acquired from 28 testers and expanded by the data augmentation. Secondly, to utilize unlabeled data, SADA combines self organizing maps with the transfer learning in predicting labels. Thirdly, SADA integrates the one-class classification with domain adaptation algorithms to reduce overfitting. Based on our enlarged database and standard databases, a large dataset of 73200 records and a small one of 1849 records are built up to verify our proposal. Results show SADA\u27s effectiveness in predicting labels and increments in the sensitivity of DNNs by 14.4% compared with existing domain adaptation algorithms

Max-SINR Receiver for HMCT Systems over Non-Stationary Doubly Dispersive Channel

In this paper, a maximizing Signal-to-Interference plus-Noise Ratio (Max-SINR) receiver for Hexagonal Multicarrier Transmission (HMCT) system over non-stationary doubly dispersive (NSDD) channel is proposed. The closed-form timing offset expression of the prototype pulse for the proposed Max-SINR HMCT receiver over NSDD channel is derived. Simulation results show that the proposed Max-SINR receiver outperforms traditional projection scheme and obtains an approximation to the theoretical upper bound SINR performance within all the local stationarity regions (LSRs). Meanwhile, the SINR performance of the proposed Max-SINR HMCT receiver is robust to the estimation error between the estimated value and the real value of root mean square (RMS) delay spread.Comment: This paper has been accepted by URSI GASS 2014 and will be presented in the proceeding of URSI GASS 201