Search

Microwave power transmission has become a hot research topic in recent years. To overcome the constrain of traditional MPT techniques, a holographic metasurface antenna which can focus the radiation microwaves at 5.8GHz band is proposed in this paper. Simulation results show that the proposed antenna has a good impedance matching and excellent focusing ability as predicted. The proposed focusing method can pave the way to promising applications in MPT area, dramatical increasing the efficiencies.

In this paper, a novel high efficiency wireless energy harvesting system based on metasurface is proposed. The periodic receiving antenna array consists of 4x4 subwavelength units with branch square loops. The receiving efficiency of the array can reaches 84%, and the maximum gain is 9.8dB. Also, a high-efficiency rectifier circuit worked at 5.8GHz is designed for the receiving array, the simulation results show that the efficiency is 70% while the input power is 16dBm. The high-efficiency wireless energy harvesting system proposed in this article is a good candidate in wireless energy harvesting to feed some low power electrical appliances.

The safe operation of maglev trains is inseparable from the health status of each component, and fault diagnosis of components is of great significance. In this paper, taking the bearing of a magnetic levitation motor as an example, a fault diagnosis method based on wavelet threshold denoising and correlation analysis combined with EMD(Empirical Mode Decomposition) decomposition and LSTM(Long Short-Term Memory) neural network is proposed. This article first compares the optimized EMD decomposition with traditional Time-frequency domain analysis to show the superiority of its performance. Then, Use the IMF component with the largest correlation coefficient obtained from the optimized EMD decomposition as the input of the LSTM neural network.Set network parameters and structure to complete the detection of bearing failure status. This paper uses a certain type of SKF bearing signal as an example to verify it. The results show that the method has a high accuracy in the diagnosis of normal status, gear fault, outer race fault, inner race fault and roller fault.

The short-term passenger flow of urban rail transit has obvious characteristics of non-linearity and non-stationarity, and the traditional prediction method has poor accuracy. Based on this, this paper proposes a VMD-LSTM combination model for the prediction of short-term passenger flow in urban rail transit and verifies it by an example. The results show that: (1) the prediction effect of the LSTM neural network is better than the RNN neural network; (2) the VMD-LSTM neural network combined model prediction is more accurate than the prediction using the LSTM neural network alone. Therefore, the combined model is suitable for the prediction of short-term passenger flow in rail transit, which helps the subway company to grasp the law of passenger flow change, so as to formulate a practical traffic management plan and improve operational efficiency.

High utility sequential pattern mining (HUSPM) is an emerging topic in data mining. Compared with the previous topics (sequential pattern mining and high utility itemset mining), HUSPM can provide more applicable knowledge, for it comprehensively considers utility indicating the business value and sequential indicating the causality of different items. However, the combination of utility and sequential brings the dramatic challenges and makes HUSPM more difficult than the previous problems. In this paper, we propose an two efficient algorithms, HUS-UT and HUS-Par, for HUSPM. The proposed HUS-UT algorithm adopts a novel data structure named Utility-Table to facilitate the utility calculation, so it can find the desired patterns quickly. The HUS-Par algorithm is a parallel version of HUS-UT based on the thread model, which also exploits two balance strategies to improve efficiency. We also conduct substantially experiments to evaluate the performance of our algorithms. The experimental results show that our algorithms are much faster than the state-of-the-art algorithms.

The temperature measurement system for switch gear based on surface acoustic wave (SAW) is gradually mature. The feedback frequency of the SAW chip represents the temperature measured by the sensor. However there is a common issue that the SAW chip feedback frequency will appear a deviation in temperature measurement after running for a period. This paper firstly research on the phenomenon of frequency deviation, then provide a method to compensate this deviation. Theoretical analysis and experimental results show the effectiveness of this method.

Due to the introduction of a large number of auxiliary monitoring equipment in smart substation, higher requirements are put forward for the performance of substation communication network. At present, there is a lack of effective methods for monitoring and predicting the traffic of substation communication network. In this paper, a communication Network traffic predicting method based on improved Elman neural network has been proposed, according to the characteristics of network communication in intelligent substation. An improved PSO algorithm is proposed to optimize the learning process of Elman neural network. The experimental results show that this method has better convergence and stability than the standard Elman network model, and can obtain higher prediction accuracy. The method proposed in this paper can effectively predict the traffic of substation communication network.

Haptic feedback is one of the important ways to sense surrounding environment. In terms of grasping objects, the haptic feedback assists in improving accuracy and assists man to recognize the shape of object. Thus, restoring haptic feedback of amputee is very meaningful and challengeable. In this paper we present a self-developed transcutaneous electrical nerve stimulator which can stimulate neuromuscular by different waveform, frequency and voltage to generate haptic feedback for the amputee. The stimulator with multiple independent channels can generate up to 8 waveforms per electrode channel and can communicate any device by Bluetooth 4.0 using our custom communication protocol to improve the stimulator reliability. In order to choose the optimal stimulus waveform, frequency, current and location, the PC software have been designed to control the transcutaneous electrical nerve stimulator. We test the transcutaneous electrical nerve stimulator in human test. By questionnaire, pretest results showed that different stimulus location can evoke different figure movements, different stimulus waveforms can evoke different haptic sensation and the human have a same sense when stimulating in the same waveform.

In the teleoperation of lunar surface sampling, a four axis robotic arm is adopted to collect lunar soils and transfer them to the sealed pot. Due to the flexibility of slender sampling arm and interval error of the joint, it is difficult to control the end-effector aligned with the mouth of the sealed pot without any feedback. In order to handle this problem, this paper proposes a method to calculate the position and normal orientation of sealed pot with respect to end-effector by using the elliptic features obtained from the monocular vision camera, based on which the angle of each arm joint is to be solved. Due to the rotational symmetry of round sealed pot, it is difficult to determine the rotations of the normal of the sealed pot. Nevertheless, considering special configuration constraints of the robotic arm, we can ignore the influence of undetermined rotation and solve the four joint angles uniquely. Thus, error of joint angles could be corrected and an effective control is exerted to the arm to guide the end effector gradually approaching the sealed pot. Finally, the effectiveness of the method is verified by experiments.

This paper describes the development and design of a novel online detector for condition monitoring of switchgears based on Modbus technology. The equipment is based on host-and-slave structure. Each salve module, which collects different sensed information such as mechanical condition, partial discharge and temperature, is installed on the target switch gear cabinet to comprehensively monitor all the connected switchgears in the substation. Once there is any potential faults happened, the defective switch cabinet can be automatically picked out by the host. Overall system construction and its practical application are proposed.

The digital filter design of a high resolution audio sigma-delta ADC is proposed in this paper. The digital system is composed of cascaded integrator comb(CIC) filter, compensation filter and halfband filter. The design of digital decimation filter bandwidth is 24KHz, the input sampling frequency is 12.3MHz, the pass band ripple coefficient is ±0.01dB, and the stopband gain decays 120dB. By optimizing the structure, coefficients and order of the digital filter, the power consumption and the area of the system are reduced effectively. The behavial simulation shows the signal to noise ratio of the digital filter SNR is 100.6dB, and the accuracy is 16bit. The Sigma-delta ADC is implemented in TSMC 0.35μm CMOS process. The post simulation shows the overall dynamic range of the sigma-delta ADC is 97.4dB.

Deficiencies of current condition assessment method were described and next generation of Dynamic Condition Vector (DCV) assessment method was introduced at first. Typical structure and common operation of combination and expansion of DCV was illustrated by models and examples. Novel and necessary conception of dynamic element, dynamic operator and quasi-matrix operator was introduced with typical structural examples. Several prototypes of DCV for transformer, circuit-breaker, isolator, transmission line and cable were given. Finally, DCV assessment application in overall process was demonstrated. Overall process barrier was analyzed. Comparisons in assessment mathematical procedure and boundary condition limitation between current assessment method and DCV assessment method were made.

To better assess the effectivity of UHF-PD sensor/system, two types of assessment procedures were established-the simple procedure and the complicated procedure. Both procedure required GTEM-Cell system and Simulation GIS/GIL. The element structure, the diagram and the signal transmission path of GTEM-Cell system and the Simulation GIS/GIL were demonstrated. The result data indicated that the discernment of the procedure was better with more tests. The procedure covered 90% of known defects or failure cases of UHF-PD sensor/system.

A fully implantable neural interface system links neural system directly to outside world that is of great interest to both neuroscientists and clinicians. Its application will benefit patients such as amputees, paralytics, and those with nerve injury or diseases. We have designed and implemented a fully implantable wireless neural interface microsystem (NeuroBITs) for multiple sites recording of peripheral nerve. The microsystem is capable of simultaneous recording from two separate sites of peripheral nerve utilizing two independent 4-channel cuff electrodes. The system is wireless switchable and rechargeable after implantation. The integrated Li-ion battery supports a 4 hours continuous working period. The system was tested to be valid after two month implantation in rat and successfully transmitted 8 channels raw data of neural waveforms from both side of the rat's sciatic nerve. Results show that the transcutaneous data link was stable over a distance up to 3 meters between the system and the host computer. This implantable neural interface system can provide not only contingency to neuroscience research, but also valuable as a diagnostic or therapeutic tool in treatment of neurological diseases and injury.

This paper introduces a method of utilizing transcutaneous electrical spinal-cord stimulation (TcESCS) to activate locomotor function of upper limb. TcESCS is electrophysiological technique to modulate neurophysical function by electrically stimulating the neural structures in spinal cord through skin, tissue, and dura. In this study, we investigate the effectiveness of different TcESCS parameters including frequency, intensity and duration of stimulating current as well as placement of electrodes. Multi-sites electrodes are placed onto subject's nape portion over spinal cord segment C5-T1. Surface electrodes are used to record the EMG signals and generate activity map of biceps and triceps brachii muslces. The result shows that TcESCS current at 10 Hz, 200 us and 25 mA is most effective for single site stimulation. The multi-sites TcESCS has a larger EMG response than single site. From the EMG map, we find that spinal cord segments C5, C6 and C7 are highly relevant to biceps brachii muscle. Segments C7, C8 and T1 are highly relevant to biceps brachii muscle.

Ever since Chinese electric power reform in 2002, different live test approaches were introduced and applied in relative industries. There were at least 26 live test approaches applied in the field of power transformation, power transmission and power distribution. The essay introduced a comprehensive dynamic and flexible effectivity evaluation system, which helped to evaluate the strengths and weaknesses of different live test approaches.

Autonomous rendezvous and robotic capturing of flying targets is widely used in many space shuttle missions and it is very crucial for on-orbit service. To perform this task, tracking and pose estimation of the flying targets is usually considered as one of the most important issues, needing to be addressed among the whole process. Taking account of the specificity of space environment such as lighting and the continuity of the rendezvous process, in this paper, we design a fast tracking and accurate pose estimation algorithm for cooperative luminaries (or retro-reflectors), to guide a safe and reliable capturing operation. Different from available target tracking or searching method, this paper defines a new comparability measure function for target appearance and utilizes the continuity of target moving to limit the target search in a predicted range of the image, which accelerates the search process. Meanwhile, the projective shape changes of each luminary due to rotation are also considered to help improve the accuracy of the target extraction. With the positions of multiple target spots obtained from the image, least square method is applied to adjust the spatial pose results iteratively, and finally accurate pose estimation is achieved. Experiments on the simulated space target, which consists of six LEDs, validate the proposed method.

As the heart of a power system, the safe running of a power transformer is important. The rate of transformer failures caused by the winding deformation remains high, therefore the study on detecting the transformer winding deformation is of great significance to avoid unexpected failures and improve the reliability of the operation in power systems. To detect the winding deformation within a power transformer effectively, people develop lots of non-destructive methods, such as frequency response analysis (FRA), short circuit impedance (SCI), sweep frequency impedance (SFI), low voltage impulse (LVI), and so on. As a novel detection technique, the SFI method is widely used for onsite tests due to its anti-jamming ability and definite standard code, but its characteristics still need be studied further. In this paper, a fast, economical, and nondestructive testing system was established to study influence factors, which included the length of the grounding line and the inside short circuit line, on SFI method during detecting winding deformation within a power transformer. The experimental results show that: 1) the longitudinal change of the short circuit line between two disks affect the tendency of the SFI curve at medium frequency band during simulating a short circuit fault within a power transformer. 2) the change of the grounding line length leads to the change of the SFI curve at high frequencies, which results in the misjudgment of the transformer winding deformation.