Dissolved gas analysis (DGA) is an effective way to diagnose the internal faults of transformer. This paper proposes a deep belief sparse autoencoder (DBSAE), which can be performed on DGA data to detect the transformer fault. The proposed method is constructed by two layers of sparse autoencoder and one layer of back propagation network. DBSAE adopts the unsupervised training to collect the features of DGA raw data, and the back propagation network with the supervised training could realize the transformer faults diagnosis. The experiments are performed on a real DGA dataset. The experimental results verify the effectiveness of the proposed method, which can extract features from the original data, and achieve a superior correct differentiation rate which reached 95.4% in average accuracy on transformer fault diagnosis.
An out-of-core domain decomposition method (DDM) based on parallel higher-order Method of Moment (MoM) is present, herein referred to as OOC-DDM, for the radiation patterns of electrically large problems. This algorithm allows the matrix be stored on the hard disk when the matrix is too large to fit in the main memory of the computing platform. The using of higher-order basis functions can further reduce the number of unknowns. Therefore the proposed method is very suitable for electrically large electromagnetic problems. Numerical results demonstrate that the proposed algorithm implementation is more efficient in time cost and memory consumption.
Micro and nano satellites are attractive due to the low development and launching costs. Carried by micro and nano satellites, synthetic aperture radars (SARs) have great potential for urban, oceanography, land use, agriculture usages. Different than conventional satellites, the payload of Micro and nano satellites is limited. This imposes great challenges on the SAR system design. Traditional SARs adopt thousands of millimeter wave integrated circuit (MMIC) components; they are bulky and power hungry. This paper investigates the feasibility to deploy the emerging technologies to shrink the volume, reduce the cost and improve the power efficiency of the SAR system. Highly integrated radar transceiver integrated circuits (ICs) are reviewed, and a SAR transceiver IC is developed. Design technologies of low-noise amplifiers (LNAs) and high-power amplifiers (HPAs) are compared and Gallium Nitride (GaN) technology is proposed. A novel micro-electromechanical system (MEMS) based delay line is also proposed for satellite SAR to reduce the system size. Existing issues and expected improvements of these technologies are also elaborated. This work shows a clear route map for the future shrinkage of SAR system, and would be a useful guideline to the development of compact SARs for micro-satellites.
Software architecture describing the structure and behavior model of system as software blueprint plays an important role in the adaptation of software. Agent with adaptive characteristic provides unique advantage for constructing self-adaptive software systems. Addressing the deficiency of software systems based on Agent in architectures and configurations, a model based on weighted relation web is presented. In this model, through monitoring and evaluating of environment for Agent the weight for relation between Agents is adjusted, and the Agent with maximum weight is selected as the cooperating Agent, enabling the Agent based software system poses adaptation in components, connectors and configurations. This approach provides a reference to others in developing Agent based self- adaptive software systems.
This paper presents a monolithic 0.8-to-18GHz reconfigurable transceiver with dual-mode of direction and conversion functions. In the direction mode, the transceiver processes the signals from 0.8 to 5GHz. While in the conversion mode, it up-converts or down-converts the signals in a frequency from 4.5 to 18GHz. An overlap of 0.5GHz exists in the two modes, so that the transceiver will be flexible in frequencies from 4.5 to 5GHz. In the RX, the two modes share the LNA, tunable LPF, and VGA. Similarly, the two modes of TX share the VGA and reconfigurable PA. The proposed transceiver was prototyped using a 0.15-µm E-mode GaAs pHEMT process. The RX exhibits gain range of 7.3 to 41.9dB, gain step of 1dB, tunable instantaneous bandwidth from 1 to 4.2GHz. The TX demonstrates gain ranging from -2.1 to 30.4dB and output 1dB compression point of 18.8dBm. The chip occupies 79.8-mm 2 area including padframe.
Background Obstructive sleep apnea syndrome (OSAS) is a major public health concern, which can predispose people to metabolic and cardiovascular diseases. It is an urgent problem in need of a reasonable biomarker in screening OSAS patients. The aim of this study is to determine the association between serum sphingosine-1-phosphate (S1P) concentrations with the presence and severity of OSAS. Methods The study included 111 obese subjects, who underwent nocturnal polysomnography (PSG) to assess eligibility for obesity surgery. Among them, 86 patients were diagnosed with OSAS, and the remaining 25 were enrolled as control cases. Serum S1P levels were detected with enzyme linked immunosorbent assay (ELISA). Demographic and clinical Information were collected and analyzed.Results There was a significant increase in serum S1P in OSAS patients compared with control subjects. Among OSAS patients, serum S1P level progressively decreased with severity of OSAS. Linear regression analyses revealed the strong negative association between serum S1P level with apnea-hypopnea index (AHI), and positive association between S1P level with lowest saturation oxygen (LSaO2). Furthermore, Receiver operating characteristic (ROC) curve test demonstrated that serum S1P showed a better predictive capacity for OSAS compared to Epworth Sleepiness Scale (ESS) and STOP scores in OSAS screening.Conclusion Serum S1P was significantly lower in OSAS patients when compared with control subjects and was negatively correlated with the severity of OSAS. Furthermore, Serum S1P also has a reasonable specificity, sensitivity and positive predictive value in the diagnosis of OSAS. Thus, serum S1P can be a potential diagnostic biomarker for OSAS.
This paper presents a method of online monitoring vacuum degree in vacuum interrupter of high voltage vacuum circuit breakers (HVVCBs) and corresponding signal processing circuit. The ring antenna is placed outside the vacuum interrupter to receive the electromagnetic signal generated by the pulse discharge. Then convert it into electrical signal and transmit to the signal processing system. The system filters the signal and amplifies it by a certain multiple at first. Record the number of processed pulse signals and the average amplitude of signals within 30s under different vacuum degrees. And then set a threshold value of amplitude and a threshold value of number. When the relevant parameters of the signal exceed the threshold values, the relay will be triggered to warn people of the decrease of vacuum degree. This method accomplishes vacuum discrimination without touching and changing the vacuum interrupter. And the system will raise an alarm when the vacuum pressure deteriorates, which is very important in application.
The Institute of Electronics, Chinese Academy of Sciences (IECAS) is developing the 50MW S-band klystron for use in linear accelerators. A klystron structure of six-cavity and single output window is adopted. The first prototype was fabricated and tested, and the test results show the design of electron optics and RF system is basically successfully. This paper describes the development and status of this device including design ideas, simulation results and recent progress.
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