Abstract:With the improvement of microsatellite technology, microsatellites with high functional density, low cost and rapid development have become research hotspots in the modern aerospace field. However, the traditional electronic system in the microsatellite is low in integration. The wiring between boards is complicated and the reliability is low. Due to the mutual constraints on quality, volume, power consumption, and performance, it is gradually unable to meet the development requirements of microsatellites. The proposed onboard integrated electronic system for microsatellites has achieved an overall improvement in reliability, power consumption and performance under the condition of limited size and quality. This article describes the development history and research status of the integrated electronic system of microsatellites. Then, it analyzes the key technologies applied in the general and flexible design of the integrated electronic system of micro-satellites. Finally, it summarizes current challenges and future development trend.

Abstract:In this paper, we propose a discriminative sampling method to select most effective samples via deep reinforcement learning for video-based kinship verification. Unlike most existing facial kinship verification methods which focus on extracting effective features with the random sampling strategy, we develop two deep reinforcement learning methods to select samples which are more suitable for learning discriminative features, so that the overall performance can be improved. Compared with the conventional kinship verification problem, video-based kinship verification has received less attention. However, this work has greater value in practical applications. When we try to use kinship verification to solve, for example, the problem of missing population, we often get video data. Compared with images, videos contain more information, and through reasonable use we will get better performance than image-based kinship verification. Specifically, our method uses three subnetworks to achieve the kinship verification task: one DQN-based sampling network to filter the key frame, one DQN-based sampling network to filter the negative sample, and one multi-layer convolutional network to verify the kin relationship. Experimental results on the KFVW datasets show the superiority of our proposed approach over the state-of-the-arts.

Abstract:Aiming at the problem of open circuit fault diagnosis of direct drive permanent magnet wind power converter, a fault diagnosis method based on generator side current distortion law is proposed. This method studies the distortion law of three-phase current under different open circuit fault types, summarizes the distortion law and designs diagnostic variables, monitors the three-phase current of generator side after low-pass filtering in real time and calculates diagnostic variables, then obtains diagnostic signals according to the diagnostic variables, and finally completes real-time fault diagnosis according to the diagnostic signals, On the basis of single tube fault diagnosis method, a method supporting double tube fault diagnosis is proposed. The experimental results show that this method can diagnose single tube fault and double tube fault accurately and quickly, with low cost, good robustness and less misdiagnosis and missed diagnosis.

Abstract:In response to the need for high-precision micro-torque measurement of the torque fluctuation of the gyroscope motor, a highprecision counter-torque measurement system based on a torque device and an angle sensor is proposed. Based on a coaxially transmitted stepped shaft structure, the external wiring is flexibly connected with spring like hairspring to reduce the elastic interference torque caused by wiring, and realize the high-precision measurement of the torque fluctuation; based on the traditional weight calibration, the static calibration and uncertainty analysis of the measurement system are carried out. The experimental results show that the system measurement accuracy is improved by 90% compared to before optimization. In the range of -10~ 10 mN·m, the measurement accuracy is as high as 0. 06%, the linearity is better than 0. 03%, and the drift error is better than 0. 5 μN·m/ 2 h, the uncertainty is better than 0. 025%.

Abstract:D-S evidence theory will produce intuitionistic conflict when synthesizing evidence with large conflict. Since most of the existing improvement methods for correcting evidence sources only make improvements from a single perspective, they cannot fully reflect the characteristics of conflict information. In order to solve this problem, a new evidence combination method based on Pearson correlation coefficient and uncertainty is proposed. Firstly, using the Pearson correlation coefficient to measure the correlation between evidences, to define the credibility of the evidence. Secondly, the uncertainty based on interval probability is introduced to modify the credibility to obtain the weight. Finally, using the weight of the weighted average of the original evidence, synthesized using Dempster combination rule. In the case analysis, compared with the classic improved method, the proposed method can effectively deal with the fusion of conflicting evidence, and the accuracy of identifying the correct proposition reaches 0. 992 0. Compared with the existing Pearson coefficient improvement method, the proposed method is more reasonable and has higher accuracy.

Abstract:Aiming at the problem of clock frequency drift in IEEE1588 clock synchronization process, a novel clock synchronization algorithm based on sliding mode control is proposed. Firstly, the state space model of the system is established according to the recurrence relationship between master-slave clock offset and drift. Then, the sliding mode control is used to reduce the clock skew and clock drift. Finally, the frequency jitter and random error in the experimental process are optimized by sliding average filter. The results show that the clock synchronization algorithm based on sliding mode control can effectively restrain the linear growth of clock skew caused by clock drift, and control the clock skew below 1 μs, thus, realizing sub microsecond network time synchronization. Compared with the traditional IEEE1588 protocol synchronization method, the proposed method provides higher synchronization accuracy.

Abstract:In the electrostatic monitoring technology for abrasive particles in lubricating oil, the amount of induced charge measured by the sensor varies with the radial positions of the abrasive particles. The traditional electrostatic sensor is incapable of determining the accurate position and number of the abrasive particles. For this reason, this article designs an electrostatic tomography (EST) highspeed data collection system based on field programmable gate array (FPGA) and realizes 12-channel signal conditioning on the basis of the electrostatic sensor array. The effectiveness and accuracy of the EST system are verified by monitoring the charged metal balls in lubricating oil. The results show that the designed EST system can meet the practical measurement requirements and the experimental results are close to the simulation results. The amount and positions of the charged balls in the lubricating oil can be estimated correctly, and the imaging quality for charged balls in different positions is relatively good. The data collection rate reaches 10 MSPs, which provides a reference for the further study of real-time nondestructive monitoring of abrasive particles in lubricating oil.

Abstract:The CSU Electromagnetic Microgravity Tower under construction is a new type of drop tower which uses the linear motor to drive the experimental cabin and uses the upthrow and drop method to generate the microgravity environment. The tiny deformation on the supporting structure is the key factor to determine whether the experimental cabin can run smoothly on the track. In order to arrange the strain sensors more scientifically and effectively to monitor it, the improved quantum particle swarm optimization algorithm is applied to the sensor placement optimization. The finite element model is taken as an example to compare and verify the validity and superiority of the three placement optimization strategies of particle swarm optimization algorithm, quantum particle swarm optimization algorithm and improved quantum particle swarm optimization algorithm in the deformation reconstruction. The average absolute error of the improved quantum particle swarm optimization algorithm is only 1. 2% of the maximum deformation. The result shows that the improved method of quantum particle swarm optimization algorithm is effective, and it also confirms that the stochastic algorithm is feasible to optimize the sensor placement for deformation reconstruction.

Abstract:In view of the fact that the vibration signal of rolling bearing under non-stationary conditions is vulnerable to the interference of velocity fluctuation, amplitude or frequency modulation, noise and other irrelevant components, which leads to the complexity of the generated time-frequency plane, and makes it difficult to identify the fault characteristic frequency of rolling bearing. A novel method based on adaptive chirp mode decomposition and ridge detection is proposed. The proposed method constructs a high-resolution timefrequency representation, improves the accuracy of diagnosis, and has very strong adaptability. Through the analysis of the vibration signals of rolling bearing with different health conditions, it is found that the proposed method is very suitable for fault diagnosis of rolling bearing under variable speed conditions, and the diagnosis effect is better than the newly developed time-frequency analysis method.

Abstract:Aiming at the problems that the decline of accuracy appears in traditional CKF under non-Gaussian noise and the slower convergence speed of the traditional MCC algorithm, an improved adaptive correlation entropy high-degree cubature Kalman filter algorithm (ADMCC-HCKF) is proposed. This method adaptively adjusts the kernel width according to the error changes of the MCC iteration process, kernel width can influence the sensitivity of the kernel parameters to the input data, thereby improve the convergence speed of the algorithm and the processing ability of non-Gaussian noise. Under the non-Gaussian noise environment, we build a SINS / CNS / GNSS integrated navigation experiment, the results show that under non-Gaussian noise conditions, the improved adaptive ADMCCHCKF algorithm shows stronger robustness than traditional HCKF and conventional MCC-HCKF, at the same time, it has batter noise reduction performance and resistance to non-Gaussian noise. In terms of filtering accuracy, compared with the HCKF algorithm, an average improvement of 9. 63%.

Abstract:Conventional model predictive control method of permanent magnet synchronous motor (PMSM) suffers from high torque ripple and speed fluctuation, which affects the ride comfort of vehicle. A model predictive control method based on state transition constraint of a PMSM is proposed. First, the state transition probability matrix is calculated based on the historical data of the switching state of the PMSM. Secondly, the constraint error is obtained according to the current switch state and state transition probability matrix. This constraint error can limit the switching state of the switch at the next moment. Then, the cost function including the state transition constraint error is formulated in the model predictive control algorithm. The optimal switching state at the next moment is searched according to the cost function. The results of simulation study and experiment show that the improved model predictive control strategy proposed in this paper has better torque and speed response characteristics in terms of speed ripple and torque fluctuation. The results show that the proposed model predictive control method based on state transition can be used in the control of vehicle PMSM. It is essential to improve the ride comfort of the vehicle.

Abstract:Reliability assessment is an important technical means to ensure the safe and normal operation of mechanical equipment. Circulating pumps used in aerospace equipment need to experience extreme environments during the rocket launch phase and the spacecraft in orbit phase. In order to study the reliability of the circulating pump in extreme environments such as rocket launch and spacecraft in orbit, a complete set of Reliability test system, several simulation experiments have been carried out, and relevant data have been collected. This paper uses time-domain characteristic parameter analysis and wavelet denoising-Hilbert envelope analysis to analyze and process the vibration signals collected during the simulation experiment. According to the analysis results, the reliability of the circulating pump is evaluated. The results show that the reliability of the circulating pump meets the requirements for use of aerospace equipment in extreme environments.

Abstract:Aiming at the non-linear standard curve of the relationship between concentration and light intensity in the ICP-AES analysis process, a standard curve fitting method based on the OLS algorithm and the improved LM algorithm is proposed to realize the accurate analysis of element concentration. Quadratic polynomial, cubic polynomial, limbek expression and Lwin expression are used as the nonlinear model of the standard curve to suit the distribution characteristics of different data. According to the loss function characteristics of each expression in the fitting process, the OLS algorithm is used to calculate the optimal fitting parameters of quadratic and cubic polynomials, and the improved LM algorithm is used to obtain the optimal fitting parameters of limbek and Lwin expressions, so as to realize the fitting of standard curve. The light intensity measured data of a series of standard samples with different concentrations of Sb, Cd, Sn, Mo Ni and Ba elements are used to carry out the standard curve fitting experiment of the above method. The experimental results show that the concentration-light intensity data of each element can be fitted to obtain a nonlinear standard curve with a R 2 above 0. 999, and the relative error of the fitted concentration of the standard curve to the known data points is within ±5%.

Abstract:Aiming at the problem that bearing composite fault features are difficult to be separated and extracted under strong background noise, a new compound faults diagnosis method is proposed in this paper based on fast independent component analysis ( FastICA), beetle antennae search algorithm ( BAS) and maximum correlated kurtosis deconvolution ( MCKD). Firstly, FastICA method is introduced for blind separation of rolling bearing multi-channel fault signals. Secondly, the deconvolution period T, filter length L and shift number M of the deconvolution algorithm for MCKD are simultaneously optimized by using BAS. Then an adaptive analysis method based on BAS-MCKD for vibration signal of rolling bearing is constructed to achieve noise reduction and feature enhancement of separated signals. Finally, the Hilbert demodulation method is used to analyze the envelope spectrum of the signal processed by MCKD to realize the identification of different types of rolling bearing faults. The analysis results of simulation and measured signals show that the proposed method can clearly extract the single fault characteristic frequency from the composite fault signal, which provides an effective solution for the complex fault characteristic extraction of rolling bearing.

Abstract:77 GHz millimeter-wave (MMW) radar technology is mature and widely used in intelligent vehicle environment perception, vehicle spacing measurement for driving safety, etc. In order to evaluate and ensure its working performances in practical use, the target kinematics parameters of 77 GHz MMW radar must be calibrated before being used. A simulated calibration method for the target kinematics parameters of 77 GHz MMW radar based on virtual instrument technology is proposed and a simulated calibration instrument based on virtual instrument is developed. The basic principle of the simulated calibration method and the main design ideas and technical parameters of the simulated calibration instrument are analyzed. A 77 GHz MMW radar sample is chosen for speed and range simulated calibration, and the uncertainty of the calibration results is analyzed and evaluated from the aspects of measurement repeatability, radar resolution and accuracy of the simulated calibration instrument. The expand uncertainty of the simulated speed and range are 0. 7 km/ h and 0. 12 m respectively (k = 2), which preliminarily verifies the feasibility of the simulated calibration method and the performance of the simulated calibration instrument.

Abstract:In order to solve the problem that the real-time performance of machine vision detection is insufficient, the line of sight is short, and the environmental adaptability is poor, which cannot meet the requirements of all-weather and multi environment operation of railway, a method of object detection in railway direct rail environment based on microwave radar is proposed. Firstly, the measurement characteristics of radar are calibrated by off-line experiment, and the error correction function of radar is obtained by data processing. Then, the railway safety gauge standard, radar measurement parameters and radar lateral measurement error are integrated to construct the gauge area under the radar coordinate system in real time, and the object after error correction is judged to be within the gauge. At the same time, the moving targets in the radar detection range are filtered and tracked. The real test results show that the radar has good detection performance, high real-time performance and good environmental applicability.

Abstract:Bend due to spanning seriously threatens the safety of subsea pipelines. Quasi-real-time detection of pipeline spanning can be achieved by using spherical detectors ( SDs) with low blockage risk and convenient launch / retrieve procedures. In this paper, via rationally arranging the accelerometer and mass distribution, the fixed-axis rotation of the SD is realized, the accurate output model of the accelerometer is formulated, and the AC component’s frequency and DC component of the recorded acceleration are accurately extracted and then used to indicate the downward bend of the spanning pipeline. By extracting the DC component from the acceleration data through peak detection or continuous wavelet transform, high-sensitivity detection of pipeline bend can be achieved. If the characteristic peak of the acceleration spectrum is a single peak, the pipeline has no bend; if the characteristic peak has a broadening phenomenon, the pipeline has bend. For a 12 m pipe, the bend detection resolution can reach 1 cm.

Abstract:In this paper, the distributed fault estimation method of more electric aircraft dissimilar redundant actuation system based on bond graph model is investigated. Firstly, the bond graph technique is used to model the redundant actuation system of more electric aircraft. Since the developed model is very complex, the computational efficiency is low and the scalability is poor. To solve these problems, the global bond graph model is decomposed into local computational independent sub-models based on model decomposition. Secondly, analytical redundancy relations (ARRs) are established for distributed fault detection and isolation based on the sub-models. Finally, a fuzzy extended Kalman filter (FEKF) based distributed fault estimation method is proposed. The simulation results verify the effectiveness of the distributed fault estimation method.

Abstract:The revision of the environmental error of the atmospheric electrostatic field ( EF) instrument is of great significance for improving the accuracy of lightning early warning. Because the existing simulation calculation methods are difficult to accurately restore the true and complex boundary conditions, the Finite Element Method is used to simulate the influence of terrain and surrounding objects on the measurement results of the EF, and revised the error of the atmospheric EF instrument in the actual environment. Compared with the existing methods, the Finite Element Method not only simulates and restores the true boundary shape, but also improves the solution accuracy and calculation speed. The results show that there is a power function relationship between the error revision coefficient of the atmospheric EF meter and the conductor distance when it is located on flat ground. In the shielding distance, the error revision coefficient of mountainous areas has a greater change rate than that of flat ground; the revision coefficient have a quadratic function relationship with the instrument position, and the revision coefficient of mountainous areas is smaller than that of flat ground. Through simulation calculations, it is also obtained that the environmental error revision coefficients of various atmospheric EF instrument stations in Laoshan are all less than 1. For different stations, terrain is the main influence factor of their environmental errors.

Abstract:In the manufacturing process of sealed electronic equipment, it is very important to detect and locate loose particles. Aiming at the problem of the large size of the equipment and the difficulty of determining the location of loose particles, parameter optimization Support Vector machines is used to locate the loose particle inside equipment. By designing a signal conditioning circuit and a multichannel signal synchronization acquisition circuit, the weak loose particle signal is processed and collected. By designing a two-stage dual-threshold pulse extraction algorithm and a multi-channel pulse matching algorithm, the signals are preprocessed to obtain effective signal data. By extracting and selecting the time domain and frequency domain features with excellent performance, to construct a locating data set. Comparing the performance of different classification algorithms on the data set, optimizing the inherent parameters of better-performed support vector machine. And finally using the optimized support vector machine locating model for physical testing. The test results show that the optimized support vector machine locating model has an average accuracy of 82. 58% in the loose particle locating test inside the aerospace power supply. The generalization ability of the locating model is good and meets the accuracy requirements of aerospace system engineering. Theoretically, this method can be extended to the research on the location of collision signals with similar generation mechanism.

Abstract:The high frequency switch tube in the power electronic circuit will generate high di / dt current in the circuit loop, which will cause serious magnetic field interference to the adjacent loop and destroy the normal operation of the circuit, especially on the PCB with compact wiring. In order to reduce the magnetic field interference between the wires on the PCB, the article analyzes the coupling coefficient expression between the loops and extracts the characteristic quantities: the ratio of the distance d between the rectangular loops to the length a1 of the coil l 1—d / a1 , the ratio of the area of the two loops—A2 / A1 , and the center offset angle of the two loops α. And then the paper uses the finite element analysis method to analyze the relationship between the coupling coefficient kand each characteristic quantity. Morever, by analyzing the simulation data through MATLAB, the relationship curve between the coupling coefficient k and (d / a1 , A2 / A1 , α) is obtained, and the criterion to reduce the magnetic field interference between the PCB circuit loops is proposed basing on it. Finally, it is verified through experiments, which provides a basis for the parameter setting of the circuit loop on the PCB.

Abstract:In this work, a Michelson interferometer based sensing demodulation scheme using an improved phase generated carrier (PGC) technique is proposed to eliminate the influence of interference amplitude on the phase demodulation of the distributed optical fiber vibration sensing system. Firstly, a high frequency carrier signal is applied to the reference fiber of the Michelson interferometer based fiber vibration sensing system to modulate the vibration signal which is acts on the sensing fiber link of the sensing system. Second, the sinusoidal and cosine terms of the applied signal can be acquired by the zero order harmonic, the first order harmonic carrier signal and the low-pass filter. Finally, the demodulated signal without the interference amplitude is demodulated by a proper transformation and the division of sine term and cosine term. The simulation results and experimental results show that the improved PGC demodulation technique can effectively eliminate the influence of interference amplitude on the final demodulation output signal.

Abstract:In order to solve the uncertainty of hotspot when airborne thermal imaging detects the surface of solar photovoltaic panels. The mechanism of hotspot is analyzed, and the equivalent circuit model of photovoltaic panels under shadow shading is constructed to obtain the partial shadow conditions. The mathematical expressions of the surface heat and output current of the photovoltaic panel are verified by MATLAB/ Simulink simulation and temperature measurement. Build a UAV hotspot simulation detection platform, change the input current and detection height to obtain a thermal imaging map of the photovoltaic panel surface, establish a segmentation function that characterizes the pixel statistical value at different temperatures, and use the K-means clustering algorithm to build a feature value database, which will be used to locate the subsequent faulty photovoltaic panel. The experimental results show that the method has the controllability of the current on the surface temperature of the photovoltaic panel, the infrared thermal imaging feature library constructed by the piecewise function-K-means clustering hybrid algorithm can accurately represent the hotspot features.

Abstract:In order to realize dynamic analysis and pattern recognition of knee joint acoustic emission signals, principal component analysis, difference test and classification test based on support vector machine were carried out to study the acoustic emission signals generated by knee joints in different stages of sitting-standing-sitting. The characteristic parameters of the acoustic emission signals were extracted into two principal components after linear changes; the difference test of the acoustic emission signals generated by the knee joint in the two motion stages shows that the result of the progressive significance of the healthy group was the principal component F1< 0. 05, the principal component F2>0. 05, the progressive significance results of the control group was less than 0. 05; The classification accuracy of the support vector machine for the acoustic emission signal of the knee joint reached 97. 9%. The results show that principal component analysis can successfully reduce the dimension of knee acoustic emission signals; the acoustic emission signals at different stages of movement are different, which is particularly obvious in the diseased knee joint; the support vector machine method can accurately diagnose and identify.

Abstract:Aiming at the problems that the backwardness of the airport surface friction tester’ s measurement and control system, the cumbersome operation of the upper computer, and the unstable data transmission, Siemens 1200 PLC is used as the lower computer control system and the Winform upper computer visual interface developed based on C#. Through TCP / IP protocol as a bridge between the two data transmission. Multi-threaded design is used to improve the efficiency and stability of data transmission, and Butterworth lowpass filter is used to filter out interference signals in the original data. The measurement system is easy to use. After the setting is completed, multiple friction coefficient measurement experiments are performed on the same road surface. The measurement results have good repeatability and the standard deviation of the average friction coefficient value is within ± 0. 02, which meets the relevant requirements of civil aviation special equipment.

Abstract:In order to solve the problem of low resolution and poor estimation accuracy of direction of arrival (DOA) when the number of microphones is small, so that designing an effective sound source localization system, this paper deeply studies and optimizes the MUSIC algorithm. The generalized cross-correlation is used to estimate the time difference between the sound source signals reaching each microphone, and building the corresponding vector signal. Finally, the DOA estimation value is determined by calculating the spectral function. The simulation and experimental results show that the optimized MUSIC algorithm can get sharper directional beam, lower sidelobe, and the positioning accuracy of azimuth angle can reach ±4° and elevation angle can reach ±5° respectively.

Abstract:Aiming at the problem of the low-frequency noise and drift error of the gyroscope that causes the accuracy of attitude measurement, this paper proposes to use the empirical wavelet transform (EWT) algorithm to fuse the gyroscope and accelerometer to calculate the attitude angle. First, use the EWT algorithm to divide the spectrum of the data collected by the gyroscope to obtain the modal components of the signal, and then use the wavelet adaptive soft threshold denoising method to denoise the signal and reconstruct the signal to obtain the processed gyroscope data. Then according to the PID complementary filtering method, the data of the accelerometer is used to correct the data of the gyroscope. Finally, use the corrected gyroscope data, combined with Runge-Kuta method to calculate the quaternion, so as to obtain the precise attitude angle by using the quaternion. The experimental results show that the EWT algorithm fused with gyroscope and accelerometer can improve the accuracy of attitude calculation by 50%, and the noise reduction effect is good, which meets the requirements of accuracy of attitude calculation.