Abstract:As the substrate of electronic devices, the printed circuit board (PCB) is in high demand. It carries the layout of circuit components and wires, which has a significant impact on the quality of electronic products. Because electronic devices are thin and compact, PCB defect detection using machine vision is difficult. This article examines PCB defect detection algorithms based on machine vision in recent 10 years from three perspectives, including classical image processing, traditional machine learning, and deep learning. The advantages and disadvantages are analyzed to improve researchers′ understanding of PCB defect detection. Nine PCB data sets and performance evaluation indexes are introduced. The advanced algorithms are compared and analyzed on PCB data sets and popular small target data sets, respectively. Finally, the current challenges with the PCB defect detection method are discussed and future research objectives.

Abstract:To reduce the influence of temperature change on the measurement results in the image-based roadbed settlement monitoring system, this article proposes a temperature compensation method for this monitoring system by studying the temperature drift of its core device—CMOS industrial camera. First, it is analyzed and explained that the temperature variation can affect the measurement accuracy of the monitoring system. Then, a drift parameter compensation model is formulated and experiments are set up for evaluation. Experimental results show that the drift parameter compensation model reduces the image point error of the camera from 1. 0 ~ 2. 5 pixel to 0. 1 ~ 0. 4 pixel, which shows the correctness of the model. Meanwhile, a comparison experiment is set up, and the compensation effect of the drift parameter model schemes is close with the compared method of system identification. But, the proposed compensation method has a simple process and is more practical. Finally, the temperature compensation method of the roadbed settlement monitoring system is proposed and evaluated. Results show that the method can improve the measurement accuracy of the monitoring system. The proposed compensation method is of great significance to improve the measurement accuracy of the image-based roadbed settlement monitoring system.

Abstract:The visuo-haptic augmented reality is a new technology that adds haptic perception to augmented reality, which helps to realize the integration of real scenes and virtual objects, as well as the synchronization of vision and touch. This article proposes a new visuohaptic interaction algorithm based on the 3D Systems Touch haptic device. Firstly, an augmented reality environment built on the Marker-SLAM algorithm is adopted to obtain positions and poses of the camera in the map in real time. Secondly, to integrate haptic information into the augmented reality environment, a tracker-free stylus tip pose optimization algorithm is proposed. Finally, the 3D information of the measurement points in the haptic and world coordinate systems is collected respectively. The forward motion model of the haptic device is mapped into the augmented reality space by determining the rigid transformation between the two coordinate systems. The registration accuracy of the tracking registration methods proposed in this article is all above 90% . Different from the tracker-based method, the average error of the corrected position obtained by the pose optimization algorithm in this article is 2. 3±0. 2 mm.

Abstract:Due to the light absorption and scattering effect of the water volume, underwater images suffer from strong attenuation, high noise and serious color distortion. Thus, the original underwater images can hardly meet the requirements of visual observation and image analysis. To solve this problem, this article proposes an underwater image restoration method based on gradient prior for improving underwater image quality. First, according to the underwater imaging prosperity a gradient prior is established for underwater images that the gradient of scene imaging information (the clear layer of underwater images) must be larger than that of scattering information ( the haze layer of underwater images). Secondly, the gradient prior is modeled with the underwater imaging model. Finally, a semi-quadratic optimization function is utilized to extract the object reflection information which generates final image restoration results. Underwater samples in UEIB and RUIE datasets are taken for experiment evaluation. In contrast to five state-of-the-art underwater image information processing methods, the proposed method obtained prominent performance in both qualitative and quantitative evaluation. The average PSNR, SSIM, and UIQM values of this method are 20. 066 5, 0. 696 1, and 3. 902 9, which are better than compared methods. Therefore, the proposed method can efficiently remove underwater image noise. The image signal to noise ratio), sharpness and the contrast of underwater images are enhanced.

Abstract:The traditional SURF algorithm using a fixed threshold in image matching has problems of uneven feature points, low matching accuracy and high time complexity. To address these issues, an improved fast image matching algorithm based on the SURF algorithm is proposed. Firstly, through the statistical analysis of the response of the Hessian matrix, an adaptive threshold method is proposed to extract more effective feature points in the image pyramid. Then, the method of quadtree is introduced to homogenize the proposed feature points to reduce the false matching rate. To prevent the quadtree from being over-split, this article proposes an adaptive split depth method to improve the quadtree. Finally, this article combines the BEBLID binary descriptor with the improved SURF algorithm for the first time, and uses the sampling mode based on machine learning to build strong descriptive binary descriptors for feature points, which improves the matching accuracy and enhances the matching speed. Experimental results show that the matching accuracy of the proposed algorithm in the Mikolajcyzk image dataset test is 9. 7% to 27. 0% higher than that of the traditional SURF algorithm, and the speed of algorithm is more than 50% . Compared with SIFT, SURF, BRISK and ORB algorithms, the improved algorithm proposed in this article has better robustness and real-time performance.

Abstract:Irregular pipes play an extremely important role in special industries. The detection of subtle defects on their inner surface faces structural characteristics, such as small space and free change of radial size, which makes the traditional in-pipeline imaging detection method has the problem of out-of-focus caused by the large change of depth of field scale when imaging in succession, and affects the system′s high-resolution imaging. To solve this problem, a method for the cross-mode full depth of field imaging is proposed, which is by focusing the imaging surface depth data and imaging system parameter data. The current focus mode is determined adaptively, and the corresponding aggregate of the focal plane depth data will be output. A radial cross-mode imaging device with a depth-sensing function is developed, and an imaging experiment is implemented for the features of fine lines in the inner wall of an irregular pipe. Results show that the designed imaging device can obtain the single focus image or fold focal sequence images adaptively, a multi-focus fusion operation in the wavelet domain is performed on the stacked sequence images to obtain the full depth of field image, and the obtained full depth of field image can distinguish tiny fine lines with a width of 0. 5 mm under the condition of a 40~ 1 000 mm depth span. The method and device can provide reliable image support for defect detection and damage analysis of irregular pipes and other similar scenes.

Abstract:Liver tumor segmentation from CT image is an important prerequisite for early diagnosis, tumor burden analysis, and radiotherapy of liver cancer. To segment tumors accurately and automatically, a deep U-shaped network based on the residual block and attention mechanism is proposed. In this network, a residual path with deconvolution and activation operations together with a convolution module is first introduced in the skip connection to separate image features and obtain their high-level representation, which ensures that the skip connections mainly transmit the information of image edges and global information of small targets. Then, the attention mechanism is introduced in the decoding path to further enhance tumor feature and suppress irrelevant information by assigning different weights to the feature information obtained by skip connections and deconvolution decoding. The global Dice coefficient achieved by the proposed method on LiTS dataset is as high as 86. 71% , which is obviously higher than many other existing methods. Compared with other methods, the proposed method has obvious advantages in segmenting tumors with small size, low contrast, and blurred boundaries.

Abstract:The images in coal mines have problems of dim, blurry and unclear edges. To address these issues, this article proposes a lightweight mine image super-resolution reconstruction method that fuses hierarchical features and attention mechanism. Firstly, by integrating the coordinate attention mechanism into the residual block, this article designs a residual coordinate attention module, which enables the network to obtain rich high-frequency detailed information. Secondly, the hierarchical feature fusion mechanism is adopted to fuse the feature map information of different network levels. Thereby, the reconstruction of edge detail information is promoted. Finally, the dimensionality reduction is performed on the fused features to reduce the amount of model computation and parameters. In addition, to make the proposed model have better generalization performance in real-mine scenes, a coal mine underground image dataset CMUID is constructed for the training and testing experiments of the network model. Experimental results demonstrate that the reconstructed image quality of the proposed algorithm is superior to other comparison algorithms in both objective indicators and subjective feelings. Compared with the OISR algorithm on the underground coal mine image data set, when the scaling factor is set to 4, the average values of PSNR and SSIM of the proposed algorithm can be improved by 0. 318 5 dB and 0. 012 6. As for the public data set, the average PSNR and SSIM of the proposed algorithm are also improved by 0. 1 dB and 0. 003 5, respectively, as well as the number of network model parameters is reduced by 70. 7% .

Abstract:In laser interference absolute gravimeter, the rotation of falling body leads to inaccurate gravity measurement. To reduce the influence of rotation error on gravity measurement, this article proposes a method that can measure the distance between the mass center and the optical center of falling body with high precision. Based on the torsion pendulum device, this method uses torsion wire to laterally suspend the falling body. By guiding and exciting the twisted wire, the falling body may twist around the twisted wire. The orthogonal interferometer is used to measure the displacement of the optical center of the falling body along the measuring direction in the twisting mode, and the photoelectric autocollimator is used to measure the angle signal of the falling body twisting synchronously. The genetic algorithm is used to deduct the influence of simple pendulum and torsion-frequency doubling component respectively. Secondly, an angle signal that decays with time is constructed to eliminate the influence of gas damping on the attenuation of the second harmonic amplitude. Results show that the expanded uncertainty of the offset between the optical center and the centroid in the direction of gravity is less than 0. 58 μm. The maximum angular velocity measured by NIM-3A absolute gravimeter is 24. 67 mrad / s, and the rotation error in absolute gravity measurement can be reduced to 0. 035 μGal.

Abstract:The precision and efficiency cannot be balanced with the existing centroid measurement methods of the large winged aircraft. To address this problem, a new mass centroid measurement method is proposed and a mass centroid testing system is designed. The system uses a laser tracker to obtain the conversion relationship between the coordinate system of the measuring equipment and the product coordinate system, which solves the principle drawbacks of the existing small-angle flip method. In this way, the measurement accuracy is fundamentally improved. The advantage of this method is that the system only needs to measure a set of product key points and reference point coordinates of test equipment, which improves the measurement efficiency compared with the existing coordinate positioning-weighing method. Simulation results show that when the tilt angle is 15°, the standard uncertainty of the centroid measurement is less than 1. 91 mm. Compared with the traditional methods, experimental results show that the error of the centroid measured by this method is reduced by about 1 / 3.

Abstract:The double-roller-guide involute measuring instrument is a kind of involute measuring instrument with no Abbey error, few error sources, and high measurement accuracy, which is commonly used to measure the class-1 gear involute artefacts or class-1 standard gears. However, it is not easy to obtain the accurate correspondence between the profile deviation and roll path length of the measured involute with the double roller-guide involute measuring instrument. The root of the involute flank is prone to accumulate machining and measurement errors, while the profile deviation of class-1 gear involute artefacts is required the to be calculated from 3 or 5 mm of the roll path length, which may lead to large profile measurement deviations if the roll path length is off. To obtain a more accurate correspondence between profile deviation and roll path length, and to achieve a more accurate evaluation of gear involute artefacts, the effect on the roll path length caused by the tip corner chamfer, deviation of tip radius and deviation of roller radius as measuring gear involute artefact with double roller-guide involute measuring instrument is analyzed. Tip corner chamfer and deviation of roller radius could lead to deviations in roll path length of millimetres. In addition, a kind of measuring strategy for a double roller-guide involute measuring instrument based on machine vision is proposed. The theoretical tip point and the starting measuring position of the gear involute artefact are obtained by machine vision and the roll path length is corrected according to the roller radius. A measurement experiment is also implemented on a gear involute artefact, the difference in the profile form deviation between the double roller-guide involute measuring instrument and the gear measurement centre is no more than 0. 1 μm, and the profile deviation curve is consistent. It shows that the measurement strategy could obtain the correspondence between profile deviation and roll path length.

Abstract:It is difficult to model the thermal error of motorized spindle accurately, and most researches just focus on the axial thermal error and ignore the radial thermal error. Therefore, a method for establishing the model of thermal error is proposed by using thermoelastic theory and mean-value theorem of integral of temperature field. The bearing temperature-thermal deformation model of the motorized spindle is formulated by using the thermoelastic theory. Then, the mean-value theorem of integral is used in the axial thermal error modeling. Therefore, a linear model of spindle temperature and axial thermal deformation is obtained, and the elongation of the end of the spindle could be achieved only by measuring the temperature of key points. The mechanism of radial and axial errors generation of the motorized spindle is analyzed to get the coupled thermal error model. A novel method for measuring thermal error of the motorized spindle by using a ballbar is presented. The feasibility is evaluated by comparing the error theoretical modeling data with the actual measurement data and the error model is imported into the developed independently external-hanging error compensator. Experimental results show that the thermal error of machining the hole’ s radial-error is reduced by about 73. 5% , which shows that the method is reasonable and effective.

Abstract:An improved point cloud simplification and reconstruction method is proposed to solve the problems of feature disappearance and hole phenomenon in point cloud scanning and sampling of thin-walled blades. Firstly, the outer contour of the blade is extracted according to the angle threshold of the normal vector and the Euclidean distance. Secondly, the average curvature and Gaussian curvature of the point cloud are calculated, the threshold is set to divide the point cloud into molecular sets, and the index space method is used to simplify the point cloud data. Then, the greedy algorithm is used to analyze the blade point cloud for the distance threshold coefficient and triangle parameters, and the empirical value of greedy triangle parameters without holes is obtained. The relationship between the distance threshold coefficient and the average distance of point cloud is fitted to realize the automatic adjustment of greedy reconstruction parameters. Compared with the other two methods, experimental results show that, when the overall reduction rate is about 90% , the standard deviation is reduced by 26. 45% and 19. 92% , and the average deviation of the outer contour dimension is reduced by 79. 81% and 47. 97% , respectively. The reconstruction parameters are set according to the proposed method, and the reconstruction quality is good, which has a good application reference for the realization of intelligent machining detection of thin-walled blades.

Abstract:To investigate the influence of temperature effect on the measurement accuracy of hydrostatic leveling system ( HLS) and reduce the measurement error, a temperature gradient test platform is established, which combines with the ambient temperature research completed in the previous stage. Researches are conducted on the HLS measurement accuracy under temperature gradient conditions, and the heating / cooling mode, temperature gradient TG variation, liquid expansion coefficient γdi and communicating pipe expansion coefficient γpi, and measuring-point distance Dtest are analyzed quantitatively. Results show that the temperature gradient influence coefficient ΔPt-G between the heating and cooling mode is only 0. 003 mm/ ℃ , which indicates the limited effect of the heating / cooling mode on the HLS measurement accuracy. The elevation of the measuring point has an obvious correlation with TG . The ΔPt-G has a linear correlation with the (γdi - γpi) and also shows the power function relationship with Dtest . Finally, a modified model for the temperature effect-induced error in HLS is formulated. The reliability and applicability of the model are evaluated by the settlement tests of the Nanjing Yangtze River tunnel and Taihu tunnel.

Abstract:The existing artificial anal sphincter system cannot supply stable, long-term and safe way of energy, which greatly reduces its practical value in medical treatment. The transcutaneous wireless energy transmission of the artificial anal sphincter system in this article can achieve the system′s energy supply. Combined with the biaxial actuated artificial anal sphincter system, mainly aimed at the short transmission distance and serious heating problems of the existing TET, the existing coil wire diameter, the number of turns, the shape of magnetic core, and the coil structure, transmission distance between the transmitting coil and the receiving coil and other parameters are optimized. Experimental results show that when the transmission distance is 20 mm, the transmission efficiency could reach 77. 64% . When the transmission distance is 30 mm, the transmission efficiency could achieve 52. 59% . The charging temperature of the optimized transmitting coil is reduced by 55. 6% . The optimized parameters could meet the performance requirements of the biaxial actuated artificial anal sphincter system and provide theoretical basis and data support for future research.

Abstract:This article proposes and implements a sampling-clockless quasi-digital frequency-key-shifting ( FSK) demodulator with a strong tolerance against carrier-frequency offset. To precisely discriminate periods of the FSK signal without a high-frequency sampling clock, quasi-digital time registers are used to construct pulse-width comparators (PWC) to demodulate the FSK signal, which are robust against the process, voltage, and temperature variation. In addition, a discrete-time differentiator is proposed and integrated into the demodulator to efficiently reject the inevitable carrier frequency offset and drift of the FSK signal. The demodulator is prototyped, analyzed, implemented, and tested. The measurement results show that the demodulator can demodulate FSK signal with a data rate of 1 Mbps and a modulation index of 0. 5, while only requiring a 10. 7 dB signal-to-noise ratio to achieve a demodulation quality with a biterror ratio of no more than 10 -3 while tolerating a frequency offset or drift in the range of -0. 56 to 0. 48 MHz.

Abstract:When the grid voltage is unbalanced, the double closed-loop PI control strategy needs to control the positive and negative sequence components of the grid voltage separately. Its parameter setting is complicated and the stability performance is poor. To simplify the control structure under unbalanced condition and improve the overall control effect of the system, a power control strategy for Vienna rectifier grid voltage reconfiguration under grid unbalanced condition is proposed. Firstly, by using grid voltage reconfiguration control to deal with the unbalanced voltage of the grid in the αβ two-phase static coordinate system, the coordinate transformation is reduced and the separation of positive and negative sequence components is cancelled. Then, from the perspective of optimizing the complexity of tuning parameters, a mathematical model of predicted power based on instantaneous power theory is formulated, and the tuning of PI controller parameters is cancelled. Finally, the comparison and analysis are implemented by building the simulation model of the predictive power control based on the network voltage reconstruction and the PI double closed-loop control strategy in MATLAB/ Simulink. Compared with the traditional PI control strategy, the analysis shows that this control strategy reduces the total distortion rate of grid-side current by about 70% under grid unbalance, and about 40% under grid unbalance and load mutation. The feasibility of the control strategy is evaluated on the platform.

Abstract:To improve the swing accuracy of the piezoelectrically driven fast steering mirror ( FSM) in the precise image stabilization system of the space telescope, the hysteresis nonlinear compensation and control technology of the piezoelectric actuator are studied. Aiming at the asymmetry of piezoelectric hysteresis and the complex inversion process of the Duhem model, the differential equation of the Duhem model is transformed, and the asymmetric Duhem inverse hysteresis model is directly formulated as a hysteresis feedforward compensator, and the immune differential evolution algorithm is used to identify model parameters. On the basis of compensating piezoelectric static hysteresis nonlinearity with Duhem inverse model, a linear quadratic Gaussian with optimal reference tracking (LQGORT) control method is introduced to further improve the dynamic performance of piezoelectric actuators. The dynamic hysteresis ratedependent auto-regressive exogenous (ARX) model is used to establish the state space equation, which is used for the Kalman filter to predict the state variable and the controller to calculate the optimal control coefficient matrix of the state variable. Experimental results show that the directly established asymmetric Duhem inverse hysteresis model can effectively describe the asymmetric inverse hysteresis curve of the piezoelectric actuator. The fitting root mean square error is 0. 635 9 V ( 0. 5 Hz), and the relative error is 0. 79% (0. 5 Hz). Real-time tracking of target displacement signals with an amplitude of 24 μm and a frequency range of 1 to 80 Hz. The tracking error of the LQG-ORT algorithm is 0. 065 5 μm, and the relative error is 0. 27% .

Abstract:The accurate sensing of the size and distribution of wear debris in lubricating oil is an important method for evaluating service condition and remaining using life prediction of mechanical equipment. However, in practical application, the output of inductive debris detection sensor is often contaminated by a variety of noise and interference, which makes a challenge to identify the characteristics of debris signals. Therefore, an adaptive method for induced voltage feature identification is proposed in this article. Firstly, the detection signal is multi-filtered by low-pass filter with different cut-off frequencies. Based on the significant difference between multidimensional filtered data, the target signals are located and segmented. Finally, according to the established mathematical model, the signal numerical features are extracted to realize the identification, counting, as well as quantitative analysis of wear debris. Experimental results show that the proposed strategy successfully extract the induced voltage generated by a 70 μm ferromagnetic debris with little distortion of morphological characteristics, which provides a basis for improving the detection performance of the sensor and accurately evaluating the wear state.

Abstract:The distance-based clustering is one of the common methods to realize the anomaly detection of telemetry parameters in complex systems, such as spacecraft. However, when it is applied to high-dimensional remote measurement data, it often exposes serious problems, such as low efficiency and degraded accuracy. To overcome the difficulty in anomaly detection on the high-dimensional telemetry data, this article proposes an improved distance definition based on coupling adaptation. The inductive monitoring system (IMS) algorithm which is a classical distance clustering algorithm is improved. Based on the intrinsic distribution characteristics of historical telemetry data, this method mines dynamically the couplings among telemetry parameters while clustering. Then, it takes efficiently advantage of this mined knowledge of telemetry parameters’ couplings into the following task of anomaly detection. Finally, this article evaluates the application of the proposed method on a high-dimensional telemetry data of a real rocket power supply system. Compared with a variety of classic high-dimensional anomaly detection methods based on IMS algorithms, this article demonstrates its advantages for high-dimensional anomaly detection as well, which is 69. 03% and 41. 83% better than the best method in other two categories of IMS algorithms respectively on efficacy and accuracy of anomaly detection. It shows the superiority of the detection methods using the proposed distance definition in efficiency and accuracy.

Abstract:The traditional threshold setting method of multi beam sonar multiple detection technology is effective for the detection of multiple echoes with the same beam amplitude. When the echo amplitude is different, the conventional threshold setting method is difficult to adapt and adjust. To address this issue, a joint weighting method based on instantaneous frequency variance and spectral characteristics is proposed to weight the echo amplitude. The instantaneous frequency variance of the echo signal is obtained by using the characteristic that the phase of the echo signal is regular. The spectral characteristics of the signal are analyzed to obtain the equivalent bandwidth of the echo signal. Using the characteristics that the obtained equivalent bandwidth value and the instantaneous frequency variance value are very low or even close to 0, the echo signal of weak target submerged by strong target signal is highlighted, which is convenient for the simultaneous detection of strong and weak targets and improves the detection ability of targets. Computer simulation results show that after joint weighting, the relative amplitude of strong and weak targets is increased by nearly 30%, and the detection ability is improved. Through the field test data processing results, it can be found that the target echo detection ability after instantaneous frequency variance and spectral feature weighting processing has been significantly improved.

Abstract:To efficiently and accurately locate the buried gas pipe leaks, a three-dimensional ( 3D) localization method for the leakinduced vibroacoustic source based on the grey wolf optimization (GWO) and the dual-wave spectrum estimation 3D is presented. A dual-wave spectral function is formulated by using the mixed signal model of P1 and S waves detected by a ground-mounted accelerometer array. The velocity is estimated by using the dual-wave velocity pairing based on the superimposing characteristic of dual-wave peaks. Then, the estimated velocity is substituted into a 3D spectral function to perform 3D localization. Considering the 3D spectral function as a fitness function, the procedures of dual-wave velocity pairing and 3D localization are optimized by using the GWO algorithm to replace the grid search for 3D spectra. Experimental results show that the presented method can accurately estimate the velocity at which the leak-induced vibroacoustic wave propagates along the soil, and thereby locating the underground leak. Compared with the conventional method using 3D spectrum search, the localization accuracy of the presented method is increased by 25. 85% , and the search time for 3D spectra is decreased by 99. 95% .

Abstract:The complex chemical process has problems of strong nonlinear, multivariable coupling, parameters time-varying and large time delay, which result in low accuracy of soft sensor. To address these issues, a soft sensor modeling method based on the regularization AdaBound interval type-2 fuzzy neural network (RAIT2FNN) is proposed. Firstly, to solve the problem that the structure of interval type-2 neural network ( IT2FNN) is difficult to determine, an algorithm for self-organizing generation rules that uses firing strength and rule similarity to define growth and deletion indicators is proposed. The algorithm uses the firing strength to determine whether to generate rules, and deletes the rules according to the similarity. In this way, the architecture of the IT2FNN is determined. Secondly, this article proposes AdaBound with regularization to modify the relevant parameters of the RAIT2FNN model. And different parameters have bounded adaptive learning rates. Finally, RAIT2FNN is used as a soft sensor model to predict the tail oxygen concentration for uncatalysed oxidation of cyclohexane process. The experimental results are that the test time is 0. 008 2, the training RMSE is 0. 018 2, and the test RMSE is 0. 009 6, indicating that RAIT2FNN as a soft sensor model has the advantages of timely prediction and high prediction accuracy.

Abstract:To promote the development of condensation particle counter (CPC) and improve its detection performance, the research of flow field simulation and flow ratio optimization in CPC particle grower are carried out systematically. The basic structure and analytical model of the particle grower are designed and established. The parameter distribution in the flow field of the particle grower is investigated by Fluent software simulation. Meanwhile, the effect of the flow ratio on the variation of saturation and the theoretical counting efficiency of CPC is considered. Simulation results show that the sheath structure can restrict the aerosol particles to flow at the position with high saturation in the central axis of the flow field. The higher the flow ratio is, the smaller the diffusion range of aerosol particles is. In a reasonable range, the increasement of the flow ratio can increase the vapor mass fraction and saturation, and the critical diameter is reduced. Under the setting of optimized flow parameters, the particle diffusion range of self-designed particle grower is only 4 mm, and the maximum value of saturation can exceed 7. The self-designed CPC measurement system is designed according to the numerical simulation information, and the calibration experiment of its counting efficiency is carried out. The calibration results show that the relative errors of 13 points within the particle size range of 7~200 nm are all lower than 9% , which fit the calibration specifications well. Thus, the design of CPC structure and optimization of operational parameters based on the numerical simulation is instructive for CPC development.

Abstract:The high-frequency bathymetric side-scan sonar is affected by Gaussian color noise. To address this issue, a direction of arrival estimation method based on the fourth-order cumulant and amplitude-phase errors self-correction is proposed. First, the fourthorder cumulant of sonar echo signal is calculated to obtain the covariance matrix. Secondly, the weighted average algorithm is used to reduce the dimension, and obtain the construction matrix after dimension reduction. Thirdly, the amplitude and phase correction are accomplished by recovering the Toeplitz properties of the construction matrix. The phase linear fitting algorithm is added to further improve the correction effect. Finally, the Root-MUSIC algorithm is used to obtain the DOA estimation. Compared with the selfcorrection Root-MUSIC algorithm, simulation results show that mean square error of the proposed algorithm angle estimation is improved by about 0. 07°, which improves the problem that the estimation accuracy of the fourth-order cumulant algorithm decreases under the condition of the amplitude-phase errors of the array elements. Compared with the self-correcting Root-MUSIC algorithm, the sea test data analysis shows that the relative bathymetric accuracy of the algorithm in this article is improved by about 0. 03% ~ 0. 08% and the bathymetric accuracy standard of 0. 75% is satisfied within the horizontal distance of 90 m. Both simulation and sea trail data prove that the DOA estimation performance of the proposed algorithm is better than the traditional algorithm under the conditions of Gaussian color noise and array elements amplitude-phase error.

Abstract:In view of the lag of universal time (UT1) products, which cannot meet the real-time requirement of users, it is proposed to fuse the ultra-rapid variation of length of day (ΔLOD) sequence with the UT1 sequence observed by very long baseline interferometry (VLBI) through the Vondrak algorithm. In the fusion process, combined with the Markov chain Monte Carlo simulation method, the weight ratio selection of UT1 and ΔLOD is studied to obtain the optimal real-time UT1 product. It fills the lack of ultra-rapid UT1 products at home and abroad, which provides data support for UT1 prediction. By using this method, the UT1 sequence of national time service center and ultra-rapid (ΔLOD) sequence of iGMAS, UT1 sequence of national time service center and ultra-rapid (ΔLOD) sequence of IGS, UT1 sequence of IVS and ultra-rapid(ΔLOD) sequence of IGS are fused respectively, and the fused data are compared with IERS C04 UT1 sequence. Results show that real-time UT1 products can be achieved after ultra-rapid sequence fusion, the accuracy of UT1 reaches 45. 91 μs and 87. 40 μs, respectively. They are better than the daily forecast products of IERS.

Abstract:With the expansion of frequency bands and power enhancement of various military and civilian radiation sources, the interference suffered by linear frequency modulated continuous wave (LFMCW) detectors has become more seriously. However, the current researches on the anti-jamming technology for the LFMCW system mainly focus on countering active jamming, and there are few studies on interference from strong radiation sources. To solve the above problems, against the background of the interference of high-power radar radiation sources, two typical radar signals including conventional pulses and chirp pulses are modeled, and the interference mechanism for LFMCW detectors is analyzed. According to the difference between target echo signal and jamming in timefrequency domain, an interference suppression algorithm combining time-frequency transform and edge detection is proposed in this article. In the proposed algorithm, the short-time Fourier transform ( STFT) is firstly used to obtain the time-frequency image of the received signal. Exploiting the periodic truncation characteristics of the pulse interference across the time axis, the interference is coarsely filtered in the time-frequency domain. Then, combined with the edge detection technology, the algorithm adopts the Sobel operator to perform convolution along the frequency axis to further filter out the residual interference, reconstruct the filtered spectrum, and extract the target information. Simulation and experimental results show that the proposed algorithm can effectively suppress the signal interference of two typical pulsed radar emitters, and the accuracy of obtained target difference frequency from the interference background is within 3% .

Abstract:Online high-precision measurement of tip clearance parameters between the labyrinth seals and the casing and axial movement parameters of labyrinth seals are the key to ensuring the safe operation and aerodynamic efficiency of turbine engines. The traditional capacitive tip clearance measurement system is sensitive to noise and cannot measure the axial movement parameters of labyrinth seals at the same time. Therefore, a “herringbone”-shaped capacitive sensor is designed, and a method for extracting the parameters of labyrinth seals’ tip clearance and axial movement parameters based on spectrum estimation is proposed. The measurement model of the herringbone capacitance sensor is established. The amplitude spectrum characteristics of the measured signal are simulated and analyzed, and the optimal spectrum line is determined. A signal processing method of adaptive frequency domain filtering based on estimation of rotation speed and signal characteristic frequency, full-period and uniform angle sampling, amplitude spectrum estimation, and binary polynomial surface fitting is proposed to realize the dynamic measurement of blade tip clearance parameters and axial movement parameters. The experimental platform for testing tip clearance parameters and axial movement parameters of a labyrinth seal is established in the laboratory environment. The calibration and measurement experiments are completed. Experimental results show that when labyrinth seals work below 1 900 r/ min, the measurement accuracy of blade tip clearance and axial movement is 18 μm and 30 μm within the measurement range of 0. 5~ 1. 5 mm blade tip clearance and ±1 mm axial movement.

Abstract:By improving the wall motion stability of the climbing robot, its engineering application ability could be enhanced. Aiming at the coupling characteristics of vibration and dynamics in the process of wall motion of the climbing robot, a climbing robot with flexible adsorption material is designed and fabricated in this article. Based on the rigid-flexible coupling principle, the kinematic recurrence relation between the rigid body and the flexible body is obtained. And the dynamic equation of the climbing robot is established by using the Lagrangian principle. A mathematical model of the degree of coupling of reaction kinetics is formulated. Through simulation analysis, it is found that the amplitude of the robot decreases by 35% by adjusting the ratio of acceleration and deceleration time under the same displacement during operation. The analysis shows that the rigid mass of the climbing robot and the elastic modulus of the adsorbent material increase within a certain range, and the degree of dynamic coupling reduces the climbing robot vibration response. Through the prototype experiment, the load capacity of the climbing robot and the stability of vacuum and flow in different movement stages are measured. The research provides the foundation for the driving control strategy and engineering application of the climbing robot.