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Micro flywheel system is commonly used in satellite attitude control system as the implementing agencies, its performance will directly affect the life of the satellite. So the brushless DC (BLDC) motor and control printed circuit board (PCB) that constitute flywheel system need to be fully tested before using them. There are still a lot of questions on traditional test process, such as inaccurate test data, complex test procedure, and high professional requirements of testers. Therefore, an automatic test equipment (ATE) for control PCB of micro flywheel was designed. Also, the system framework, including hardware and software specific implementation methods were introduced. Finally, experiments have shown that the system can effectively make the testing process automatic and improve the test efficiency and result accuracy.

© 2015 IEEE. A novel hybrid model is proposed in this paper to describe the highly-nonlinear hysteretic relationship between the torque and angular velocity in a magnetorheological pin joint (MRP). The MRP's hysteresis loop is modelled by a mixture of hyperbolic and Gaussian functions using the curve fitting technique, resulting in a significant reduction of the model parameters. To identify the model parameters, an immune particle swarm optimization (IPSO) algorithm is employed using torque-angular displacement/velocity experimental data recorded under various loading conditions. To demonstrate the accuracy of the proposed model and the effectiveness of parameter identification process, characterization test data of the smart pin torque and angular velocity are utilized for comparison.

The major cause of failure of high voltage apparatuses is the presence of partial discharge in insulation structure. Different types of partial discharge existed in power apparatus, which will lead to breakdown of insulation. The purpose of the research work presented in this paper constitutes the issue of effective and efficient recognition of different types of partial discharges. First, partial discharge activity under AC is studied using acoustic emission technique. The wavelet technology is used to analyze acoustic signal caused by PD. Then a hybrid model which combined wavelet transform with wavelet network is proposed to classify and characteristic different types of signals. By using this method the surface, plane-plane, pin-plane, and floating discharge signal is classified effectively. Finally, to demonstrate the effectiveness of the proposed classified method, this study investigates its identification ability using 150 sets of acoustic signals generated by the PD model in insulation oil. The experiment results show that the proposed method is efficient and reliable.

The partial discharge is one of the major failure mechanisms for insulation of power equipments subjected to high electrical stress. In order to understand the service conditions of insulating materials, it is very important to investigate on partial discharge characteristic in electrical apparatus. In the present paper, a set of acquisition system for acoustic signal generated by partial discharge is established in laboratory. The acoustic emission signals are generated by pinplane electrodes in oil insulation system in the voltage range of 4-6kV, the distance between electrodes and sensors in the range of 10-15cm. The test results show that voltage applied and distance between sensor and pin-plane regularly influence energy distribution of acoustic signal in different frequency component. The discrete wavelet transform is used to analyze acoustic signal acquired. A feature extraction method to classify partial discharge and a new method to identify different types of acoustic signal based on combined wavelet network and wavelet transform are respectively suggested.

Within the framework that two filters are working in parallel, Stochastic Taps NLMS (ST-NLMS) effectively chooses only active taps for adaptation, resulting in a good transient behavior when identifying long, sparse, echo path like systems. However, ST-NLMS still suffers from the inherent limitation of LMS. This necessitates a compromise between the opposing fundamental requirements of fast convergence rate and small misadjustment. Following the same block diagram as ST-NLMS, the Stochastic Step-size NLMS (SS-NLMS) scheme is proposed and integrated into the ST-NLMS framework. The combination leads to a novel algorithm called STS-NLMS, which adjusts step-size and active taps simultaneously. Extensive experiments demonstrate that substantial improvements in the speed of convergence are achieved by using the proposed algorithm in stationary environment outperforming both NLMS and ST-NLMS with the same small level of misadjustment. In addition, the proposed algorithm shows superior tracking capability when the system is subjected to an abrupt disturbance. Furthermore, if nonstationary environment is considered, the performance of the proposed algorithm is still satisfying.

An efficient adaptive filtering algorithm for network echo cancellers is proposed in this paper. Employing the primary and auxiliary filter that operate parallel, an algorithm recently proposed named stochastic taps NLMS (ST-NLMS) estimates and locates the active region of the unknown system impulse response, therefore results a rapid transient behavior while estimating long, sparse, echo path like system. However, ST-NLMS still fails to give satisfactory estimation of effective system response region, hence leads to prohibitive computational complexity and further enhance potential. In this paper, based on the analysis to ST-NLMS, a new algorithm named ST-NLMS++ is proposed, which originally adopts hybrid active taps re-initialization and fake active tap elimination to enhance the estimation of active tap region. In stationary environment and small step-size assumption, theoretical examination reveals that ST-NLMS++ leads a superior estimation of effective impulse location and achieves faster tap-weight convergence as well as the same level of misadjustment compared to ST-NLMS and traditional NLMS. Experiments further verify the analysis and demonstrate that the tracking performance of proposed algorithm is also satisfying in both stationary and non-stationary scenarios

General dynamic analysis for fluid flow in microchannel was presented. A microfluid flow measuring system is set up for experimental study, then the microfluid flow behaviour in microchannel with different cross sections and characteristic size is investigated under the pressure difference ranged from 0-200Kpa. The Silicon nozzle/diffuser elements are fabricated and the flow directing property of them is investigated under 0-10 Kpa . The experiment results agree well with the expected.