Abstract:The power supply system is an essential subsystem of spacecraft, which is used to generate, store and distribute electric energy. With the explosive growth of the number of spacecraft, the modeling and simulation of power supply has become a research hotspot in the field of spacecraft health management, intelligent operation and maintenance. In view of this, this article firstly summarizes the classification, composition and development trend of spacecraft power supply. Then, from the perspective of spacecraft health management and intelligent operation and maintenance, spacecraft power supply modeling and simulation technology framework, mechanism modeling, data-driven modeling, digital twin fusion modeling method of typical components, spacecraft power supply simulation technology and software, typical application of modeling and simulation are reviewed. Finally, the technical challenges and development trends of spacecraft power supply modeling and simulation are summarized and analyzed. This article is expected to provide some references for researchers in the fields of spacecraft power supply health management, spacecraft power supply modeling and simulation, and digital twins.

Abstract:To solve the problem of low accuracy of the fan state prediction model when the power plant load changes, a dynamic integrated state prediction method based on convolutional neural network ( CNN), long short-term memory ( LSTM) network and attention mechanism (AM) is proposed. Firstly, the CNN is used to divide the sample data into different classes with overlapping boundaries to achieve soft classification of wind turbine operating conditions. Then, the AM layer is introduced into the traditional LSTM network. LSTM-AM networks as sub-learners are established under different work conditions. The soft classification labels output by CNN are used as the initial weights, and the genetic algorithm is used to search for the optimal weight bias. Finally, the output of each sub-learner is multiplied with corresponding weights and summed to obtain the integrated prediction value, which could improve the prediction accuracy under different operating conditions of power plant fans. The experimental results show that, compared with each LSTM-AM sub-model and signal LSTM-AM model, the proposed CNN-LSTM-AM dynamic integrated model can reduce the relative mean square error by 11. 5% and 22. 3% when power plant fans are operating under variable loads. Results indicate that the model has better robustness and applicability

Abstract:In practical engineering applications, rotating machinery typically operates under normal conditions, which can result in nonideal datasets with few or even partially missing fault samples. To address the low accuracy issue in deep learning diagnosis models trained directly on non-ideal datasets, a fault diagnosis method that incorporates finite element simulation to facilitate transfer learning is proposed. Firstly, vibration signals with different operating conditions and fault types are derived via numerical simulations. Subsequently, a large number of cost-effective and high-fidelity simulation samples are employed to pre-train a diagnostic model, and the authentic limited dataset or the hybrid dataset augmented by simulation samples is employed to fine-tune the pre-trained diagnostic model. This approach aims to implement high-precision fault diagnosis and mitigate the reliance on actual or experimental fault data. Finally, two bearing datasets are used to evaluate the effectiveness of the proposed method. Results show that the diagnostic model constructed via the proposed method achieves an accuracy exceeding 95% with a sample size of one for each fault category. In addition, in cases where the fault samples are limited and certain types of faults are missing, the accuracy is boosted by over 10% compared to the approach of supplementing the simulation samples directly.

Abstract:AC contactors are widely used in power systems. The accurate reliability assessment of AC contactors is essential for ensuring the safe and stable operation of the system. The existing reliability studies on AC contactors did not consider the competing failure and degradation correlation among the three-phase contacts as well as the randomness of the failure threshold of each contact, which may lead to inaccurate reliability evaluation result. To solve these problems, a performance degradation model incorporating the competing failure, the degradation correlation, and the randomness of the failure thresholds is formulated by using the cumulative arc erosion amount to characterize the performance state. A multistage parameter estimation method based on the maximum likelihood estimation is presented for the problem that there are many model parameters and it is difficult to estimate all the parameters simultaneously. A reliability approximation method is provided based on the Monte Carlo technique, and an approximate expression of the mean time to failure is derived based on the technique of Riemann sum. Finally, the effectiveness of the proposed method is evaluated by simulation and real case studies. The real case study shows that the proposed reliability evaluation method has high accuracy, and the goodness of fit is about 45% better than the existing methods.

Abstract:To effectively suppress the artifacts of reflector echo with non-goal mode, this article proposes a full-skip total focusing method (FSTFM) imaging technology weighted by circular statistic vector threshold (CSVT) for surface-breaking cracks. The circular statistical vector (CSV) is established from the delayed signal. Then, the range of CSV value for the artifacts is determined by using Weibull distribution. After that, the CSVT factor is obtained by eliminating the artifacts with the threshold. Research shows that, in the effective elements range of 32~ 64, the CSV value of noise for artifacts of reflector echo with non-goal mode is 0. 2 ~ 0. 4, and the CSV value of surface-breaking cracks with TT-TT mode (goal mode) is close to 1. Therefore, the value of CSVT factor after threshold processing can effectively retain the weight factor of the defect, and suppress the most artifacts of reflector with non-goal mode and the noise with random phase distribution. Compared with full skip TFM imaging with shear wave, in the CSVT-TFM image for artificial notch orientation within -45° to 45°, the signal-to-noise ratio for artificial notch tip on the upper surface of the aluminium block is improved by range of 7. 7~ 14 dB.

Abstract:To address the problems of high-speed railway perimeter intrusion detection such as complex surroundings and a large number of small targets, an improved ByteTrack algorithm is proposed to realize the identification and tracking of perimeter intrusion. The model is improved by integrating YOLOv7-X and the data association method of BYTE. The convolution block attention module is introduced to improve the recognition effect of foreground targets in complex surroundings. The space-to-depth layer and the non-strided convolution layer are used to optimize the step convolution and pooling layers to improve the loss of fine-grained information caused by down-sampling in small target recognition. The railway perimeter intrusion dataset is established for experiments. The experimental results show that the AP of the improved module is 95. 6% , an increase of 9. 4% , and has improved the AP of target recognition for large, small, and medium-sized targets, especially for small targets, with a significant improvement of 22. 2% . The improved ByteTrack algorithm can realize the identification and tracking of intrusion behavior in the complex environment of high-speed railway perimeter, and provide technical support for high-speed railway perimeter protection.

Abstract:In view of the influence of industrial users′ industry attributes on their power consumption patterns, a power consumption anomaly identification method considering industry relevance is proposed in this article. Based on the real industrial consumer power consumption data, the typical load characteristic curves of each industry are generated, and the improved grey correlation degree algorithm is used to calculate the relevance between the power consumption characteristics of power users and the typical power consumption characteristics of the industry. In this way, the industry relevance characteristics of users are achieved. The multi-head attention (MHA) is used to extract the features contained in load sequences. Combined with the industry relevance features, the reconstruction error provided by the variational autoencoder (VAE) is used as the anomaly decision metric to formulate the MHA-VAE depth anomaly detection model to identify various types of industrial users′ power consumption anomalies. Results show that, the accuracy, detection rate and false detection rate after introducing users′ industry relevance are 96. 84% , 98. 02% , and 4. 35% , respectively. Compared with only considering the load characteristics of users, the accuracy is increased by 1. 06% and the error detection rate is reduced by 2. 24% .

Abstract:The ablation fault in the buffer layer is one of the main factors of high-voltage cable fault. Due to the complex on-site environment and the need to achieve a certain angle of relative rotation for CT detection of objects, there is no equipment for CT detection of high-voltage cables in service at present. A portable detection system for on-site application is designed by using the local CT imaging mode of X-ray source translation scanning and verified by experimental simulation and experimental platform, which realizes online CT detection of defects in high-voltage cable buffer layer in service. For the buffer layer of 110 kV high-voltage cable, the hole defect of Ø1 mm can be detected, and the defect of Ø2 mm can be detected for 220 kV high-voltage cable. After collecting 2 016 CT images with defects, combined with 802 circumferential CT images of cables with the similar structure, the method of migration learning is used to achieve automatic defect detection, with an accuracy rate of 87. 6% , a recall rate of 93. 5% , and a missed detection rate of 6. 5% , which are close to the level of circumferential CT.

Abstract:The level of decision-making intelligence of heavy-duty hexapod robots in the field terrain needs to be improved. However, if robots have not yet formed a reasonable decision structure level, the conventional decision-making reinforcement learning which is directly interact with the environment, will lead to the robot′s decision-making being too divergent. Therefore, this article first obtains the driver′s decision-making experience model through a step-training neural network which conforms to the driver′s decision-making habits. Hence, the robot can quickly form decision-making intelligence. In addition, to better play the advantages of human-robot decision-making, this article proposes a method to eliminate the conflict of human-robot coordinated decision-making commands based on the cooperative game theory. A semi-physical simulation experiment system for human-machine collaborative decision-making of heavyduty hexapod robots is designed and established. After carrying out experimental verification around the proposed methods, results show that the robot can approach the driver decision-making effect by learning the driver′s prior model and reinforcement training, and the effect of the human-robot collaborative decision-making commands can also make up for the defects in unilateral decision-making. In the regular ditches terrain, the collision index of the collaborative decision commands is 23. 8% better than that of the single driver agent commands; in the obstacle terrain, the energy consumption index of the collaborative decision commands is better than that of the single robot agent commands by 34. 1% .

Abstract:To improve the accuracy of geometric modeling of the telerobot virtual environment, a method for correcting the geometric modeling of the telerobot virtual environment based on the visual-tactile fusion is proposed. Firstly, based on the visual information, the geometric modeling of the target is realized through point cloud acquisition and preprocessing, point cloud registration combined with thick and thin registration, surface reconstruction and pose measurement. Then, aiming at the application background of telerobot, a dexterous hand control mode combining local semi autonomy and multi finger cooperation is designed to complete the collection of target tactile point cloud. Finally, the visual-tactile fusion method is used to fuse the visual point cloud and the tactile point cloud through KDtree, and the visual-tactile fusion point cloud is used to modify the geometric model. Experiments show that the geometric dimension error of the geometric modeling of the target with different materials by this method is less than 3. 6 mm, the positioning error is less than 6. 8 mm, and the attitude angle measurement error is less than 4. 3°. The effectiveness is better than the geometric model based on visual information and the geometric model based on tactile information. The geometric model constructed by this method not only includes the color information of the target, but also improves the accuracy of the geometric model. It performs well in the details of the model, which effectively combines the advantages of visual and tactile modal information.

Abstract:Foot drop is the phenomenon that ankle joint cannot produce dorsiflexion and the toe lifting is incomplete or impossible due to nerve control dysfunction. The functional electrical stimulation (FES) is used as a treatment method to correct foot drop gait, which uses low-frequency pulse to stimulate tibialis anterior to cause muscle contraction and dorsiflexion of ankle joint. The FES output intensity modulation method based on EMG modulation and iterative learning control (ILC) is proposed in this article. The angular velocity signal of the lower leg is used to predict the EMG of tibialis anterior in healthy gait through the dynamic BP neural network, and the toe pitch is used as feedback signal to output the reference EMG through ILC. The reference EMG and the EMG predicted by neural network are weighted-average to obtain the modified EMG. Finally, the FES output is modulated by the muscle activation characteristics. The experimental results show that the toe pitch angle in open-loop EMG modulation mode is only about 17°. Through the closed-loop modulation mode, the maximum toe pitch angle is about 21°. By analyzing experimental data. It can be concluded that the system can help patients with foot drop to carry out rehabilitation training.

Abstract:To address the problems of low pass rate and sudden change in speed of unmanned vehicles using the traditional timed elastic band (TEB) algorithm in a narrow space environment, a pose auxiliary point TEB algorithm (pose auxiliary point TEB, PAP-TEB) is proposed. By adding pose auxiliary points on both sides of the narrow space, the fixed-point planning algorithm is used to improve the passing rate of the narrow space environment. Secondly, the output speed of autonomous navigation and fixed-point navigation is optimized by using speed interpolation control and S-shaped speed planning. The method guarantees the smoothness of the output curve and the stability of the navigation process. Finally, the performance of the PAP-TEB algorithm is evaluated through the comparative simulation test of the unmanned vehicle operating system and the two-wheel differential unmanned vehicle experiments. Results show that the pass rate of the PAP-TEB algorithm is increased by about 50% in the 55 cm narrow channel scene. In the through-the-gate experiment, the PAP-TEB algorithm improves the pass rate by more than 20% compared to the traditional TEB algorithm, and the smaller the width, the more obvious the lifting effect. In addition, the fluctuation of the speed curve of the unmanned vehicle is small, and the smooth motion of the unmanned vehicle can be realized.

Abstract:To address uncertainties which have influence on trajectory tracking of quadrotor unmanned aerial vehicle (UAV), such as internal and external disturbances, model errors, this article proposes an integral sliding mode control program based on the improved extended state observer. In particular, we firstly regard the uncertainty factors in the quadrotor UAV system, including model error, internal and external disturbances as lumped disturbances. The improved extended state observer is used to observe them. Furthermore, on this foundation, the control continuity of the quadrotor UAV system additionally is considered. An integral sliding mode controller is designed, which is based on trajectory error, velocity error, attitude angle error and attitude angular velocity error of the quadrotor UAV. The system stability is analyzed. The numerical simulation and real machine experiment are conducted. Results show that the tracking errors of each state in numerical simulation do not exceed 1% and the tracking accuracy is the highest. In actual machine experiments, the position tracking error can be controlled below 20% by using the proposed algorithm. For this reason, the proposed method in this article is efficacious and workable.

Abstract:To ensure and improve the field measurement accuracy of the rotary table angular measurement system, a research on the separation and compensation method of rotary table indexing error based on Fourier transformation is proposed. Based on the proof of principle of Fourier transformation to separate the indexing error of the rotary table, the function model between indexing error of the rotary table and the measurement value of the reading head is formulated. According to the nature of transfer function in Fourier transformation, the relationship between the installation angle interval of the double reading head and the harmonic order of the measurement error is highlighted. The arrangement of the double reading head is optimized. The measurement value of multiple reading heads is realized on the field programmable gate array (FPGA) circuit platform. The simultaneous acquisition of the measured values of multiple reading heads is realized in the FPGA circuit platform, and the harmonic error function is calculated in real time by using the coordinate rotation digital computer. The experimental results show that the indexing error can be separated and compensated by using the optimized double reading head signals, the peak value of indexing error of rotary table is reduced from 57. 58″ to 3. 36″, and the expanded measurement uncertainty of angle measuring system of compensated rotary table is 0. 9″(k = 2).

Abstract:In the process of integration of processing and measurement, the optical on-machine measurement accuracy is seriously affected by the oil film formed by cutting fluid remaining on workpiece surface. The existing error compensation methods generally require the prior information of the oil film, such as composition, thickness, etc. Nevertheless, this information is hard to obtain in real time due to factors of processing and random distribution of cutting fluid. For these reasons, a displacement error compensation method for surfaces with cutting fluid adhesion based on multi wavelength laser is proposed in this article. First, a multi wavelength laser measurement system is designed and set up based on laser triangulation, which can measure the displacement of the same measured point by using multi wavelength laser. Then, the Cauchy dispersion law is introduced to establish the analytical relation between the optical system and the laser wavelength. Next, the inherent difference property of multi wavelength laser measurement is deduced, and the error compensation is realized. Experiments are performed according to the method in this article. The experimental results show that the absolute value of measurement error after compensation is less than 0. 01 mm. Compared with the uncompensated measurement data, the error is reduced by at least 92% .

Abstract:To improve the development of coordinate measuring machine ( CMM) and the whole machine accuracy design level, a CMM accuracy assignment method based on interval hierarchical analysis is proposed. First, the CMM quasi-rigid body model is formulated. Based on CMM target accuracy and travel range, full-parameter, high-precision solution of the quasi-rigid body model using the least absolute shrinkage and selection operator ( LASSO) and orthogonal trigonometric decomposition, the 21 geometric errors of the CMM are achieved. Then, according to the CMM structure and movement, the accuracy hierarchy of the CMM whole machine is divided. The interval hierarchical analysis is used to determine the accuracy assignment weight vector of CMM critical parts relative to geometric errors. The accuracy assignment results of CMM key components are obtained by using the CMM with the 21 geometric errors and the accuracy assignment weight vector. The results show that, for a CMM with a target accuracy of (4. 5+L / 400) μm, the prototype assembled using the proposed accuracy allocation method achieves an accuracy of (2. 7+L / 400) μm. Therefore, the proposed CMM accuracy allocation method can provide a more accurate basis for the accuracy selection of key CMM components. The accuracy of the whole machine is improved, the efficiency of the whole machine design is saved, and the research and development cost are reduced.

Abstract:This article proposes and designs a four-nozzle ejector with different nesting methods to meet the variable flow requirements of proton exchange membrane fuel cell full power hydrogen recirculation under different working conditions. The computational fluid dynamics method is used to study the internal flow field of the different nesting type four-nozzle ejectors and recycling performance. The results show that the internal flow field of partially nested ejector is more stable than that of the fully nested ejector. When the secondary flow pressure and back pressure remain constant, the entrainment ratio (ER) of partial nested ejector firstly rises and then decreases with the condition of the primary flow pressure increasing from 6 bar(1 bar = 100 kPa) to 10 bar where the maximum ER is obtained at the primary flow of 7 bar. Through the comparison with the experimental data, the partial nested ejector has better performance than the fully nested ejector whose performance of ER declines gradually in the whole process. Finally, the full power variable flow linear regulation performance is realized through the multi-nozzle logic control to meet the requirements of fuel cell variable power operation for the hydrogen cycle ejector.

Abstract:The installation errors have great influence on the measurement results of gear measurement center (GMC). Focused on the problem of the ZC1 worm helix deviations evaluation method, based on the measurement principle of ZC1 worm helix in GMC, the influence mechanism of installation errors on worm measurement is analyzed. The installation error correction model is formulated, and the evaluation method of ZC1 worm helix deviations based on installation error correction is established according to the definition of helix deviations. The measurement of ZC1 worm helix deviations is implemented on the GMC, and the helix deviations evaluation results are obtained under the installation conditions. The maximum difference between the measurement results before and after the installation error correction is reduced from 76. 2 μm to 4. 2 μm. The ZC1 worm helix deviation evaluation method proposed can effectively eliminate the influence of installation errors on the helix deviations measurement results during the measurement of GMC.

Abstract:The vertical measurement method is simple and effective to observe the displacement of dam deformation, which has been widely used in the actual dam deformation monitoring. To solve the problem that most of the existing pendulum telecoordinometer can only measure the two-dimensional displacement of the pendulum line and the structure is complex, a 3D pendulum line measurement method based on linear structured light is proposed in this article. Based on the fact that pendulum line direction keep constant, this article uses the principle of linear structured light measurement to achieve pendulum line three-dimensional displacement measurement. Firstly, the two-dimensional displacement of the pendulum line is obtained by the linear structured light measurement. Then, based on the fact that the imaging light of the fixed mark points on the pendulum line intersects the pendulum line at one point, the threedimensional displacement measurement of the pendulum line is realized by synthesizing the two-dimensional measurement results of the pendulum line and the imaging light equation of the fixed mark points recovered by the camera internal parameters. The experimental results show that the displacement measurement accuracy of this method is ± 0. 1 mm in the Y direction of the horizontal plane, and ±0. 05 mm in the X direction and Z direction of the horizontal plane, and the measuring range is 0~ 80 mm. Compared with the current vertical displacement measurement method, the vertical displacement measurement accuracy and measuring range are higher, and the measurement structure is simpler.

Abstract:The variant aircraft will change the wing structure and skin shape on a large scale when performing different flight tasks. The large-scale deformation reconstruction of the skin multi-dimensional is a difficult point in the research of deformed aircraft. To solve this problem, this article proposes a deformed shape reconstruction method for the deformed aircraft skin based on multi-core optical fiber sensing. Based on the principle of multi-core fiber grating strain sensing, this method uses multiple grating sensing points on the sensor to establish the conversion relationship between grating wavelength drift and curvature, which realizes three-dimensional curve reconstruction. In addition, to reconstruct the shape under the multi-dimensional large-scale deformation of the variable configuration aircraft, this article studies the transformation of the reconstruction curve into the unfolding angle and flip angle of the aircraft wing, and combines the inherent parameters such as the two angles and the length and width of the aircraft wing, and continuously integrates the deformation caused by the change of the two angles by fitting the interpolation, so as to realize the multi-dimensional large-scale deformation reconstruction of flexible skin. Meanwhile, to reduce the error caused by temperature, this article uses the characteristics that the intermediate fiber core of multi-core fiber is not stretched and compressed, and is only affected by temperature, and the center wavelength drift of the intermediate fiber core and the side shaft core is differentiated, so as to realize temperature decoupling. To evaluate the effectiveness of the proposed deformation reconstruction method, the deformation of the aircraft skin under different conditions is experimentally tested, and the deformation reconstruction results are compared with visual measurements. The results show that the average error of multi-dimensional large-scale deformation reconstruction of aircraft skin is 7 mm, and the average error of deformation angle reconstruction is 3. 6% , which can realize multi-dimensional large-scale deformation reconstruction of modified configuration aircraft, and this method has good application prospects in the field of structural deformation monitoring such as aerospace vehicles.

Abstract:This article proposes a novel advanced detection method with excavation in coal mine roadway, which provides a feasible idea for the parallel operation of roadway excavation and advance detection. First, the scheme of advance detection with excavation is proposed, which uses the cutting head of the roadheader as the field source with excavation to integrate the geophysical prospecting method with the main body of the roadheader. Then, the theoretical model of advance detection with excavation is formulated to obtain the change law of the potential of the measuring point and compare it with the finite element calculation results. The accuracy and feasibility of the numerical calculation method of the measured point potential are evaluated. Finally, the diversion rules of the field source are determined, and the normal geological body is taken as a reference. The evolution law of the apparent resistivity of two different types of abnormal bodies, low resistivity and high resistivity, are compared and studied. When the field source is close to the low resistance water-bearing zone, the reduction for the average value of apparent resistivity is from 5. 40% to 29. 80% . If it is close to the high resistance fault, the average value of apparent resistivity increases from 7. 12% to 35. 53% . The water tank simulation experiment is carried out, and the results show that the proposed advance detection method with excavation in coal mine roadway can detect the geological conditions in front of the excavation face in real time and continuously.

Abstract:To meet the requirements of high-precision pressure measurement in various applications, such as liquid and gas, a mediumisolated MEMS resonant pressure sensor is designed. To reduce the pressure transfer losses and nonlinearities during oil-filled packaging, the structural parameters of the corrugated diaphragm are simulated and optimized, and the diaphragm parameters suitable for the sensor core are determined. By using MEMS processing technologies and vacuum micro-filling methods, the MEMS resonant pressure sensor chip production and oil-filled packaging are completed. The dual resonator pressure and temperature multi-parameter co-sensing methods are utilized, and the temperature self-compensation is realized without the addition of a temperature sensor. The test shows that the accuracy of the packaged sensor is better than ±0. 01% FS, hysteresis error is better than 0. 006% FS, nonlinearity error is better than 0. 003% FS, and repeatability error is better than 0. 008% FS in the operating temperature range of -55℃ ~ 85℃ .

Abstract:As one of the common measurement equipment of primary side current, the current transformer plays an important role in AC current measurement, relay protection, power equipment maintenance control and other related fields of the power system. To address the problems of low linearity, poor anti-interference ability and low precision existing in traditional current transformers, it is especially difficult to accurately measure the low power frequency current. In view of this, a fiber optic current transformer based on the MachZehnder interferometer is proposed in this article. The transformer uses the Joule heat generated by the current passing through the resistance to change the optical signal characteristics in the fiber to cause the change of the output signal of the Mach-Zehnder interferometer. Then, the optical signal of the interferometer is captured by the photodetector and converted into electrical signal output to complete the power frequency small current detection. In the structure, the PCB-type Rogowski coil is adopted as the induction device, and its dynamic response analysis is completed by MATLAB. In addition, a signal processing system based on FPGA technology is designed to improve the signal to noise ratio. Finally, the small power frequency current is measured through the experiment. The linear correlation coefficient is 0. 996 1, and the detection accuracy can reach 0. 14% . The experimental results show that the proposed fiber optic current transformer has higher linearity and measurement accuracy than the traditional optical current transformer, which provides a new idea for the development of current transformers based on thermal effect. It also provides a new method for the measurement of power frequency small current.

Abstract:Due to the difference in the properties of gas and conductive fluid, the presence of gas in conductive fluid may affect the output characteristics of the magnetohydrodynamic micro-angular vibration (MHD) sensor. Based on electromagnetic induction theory and twophase flow theory, the volume of fluids (VOF) model of the MHD sensor containing gas in conductive fluid is deduced and established. ANSYS fluent is used to simulate and analyze the output characteristics of the MHD sensor with gas. An experimental platform is established to verify the MHD sensor with different gas content. The results show that the bubble in conductive fluid is easily torn into small bubbles at low frequencies and disperse with angular vibration, which causes the flow field and electric field of the fluid to shift and distort. The lower the frequency of angular vibration, the more obvious this phenomenon is. When there is no gas in conductive fluid, the external factors such as angular vibration frequency and amplitude, gravity acceleration and eccentricity have no influence on the output characteristics of the MHD sensor. When the conductive fluid contains gas, the output characteristic distortion of the MHD sensor increases with the increase of gas content, gravity acceleration and eccentricity, and decreases with the increase of angular vibration frequency and amplitude. The research results of this article can provide guidance for the filling process control of the MHD angular velocity sensor and help to improve the accuracy and stability of the sensor

Abstract:Real time monitoring of combustion temperature field and flue gas velocity field in boiler is important to ensure the operation of boiler safely and economically. The acoustic tomography (AT) is considered to be a non-intrusive and effective method that can give information about temperature distribution and flow field. In this article, a novel method based on AT technology is proposed to reconstruct the temperature and velocity fields simultaneously. A multi-physical field reconstruction model based on radial basis function is formulated, and the Tikhonov regularization algorithm is used to solve ill-posed problems. In addition, we consider the refraction effect of the sound waves in the process of reconstruction. The numerical simulation results show the effectiveness of the proposed measurement method in simultaneously reconstructing the complex temperature distribution and velocity field. When the refraction effect of the sound waves is considered, the method can significantly improve the reconstruction quality of various physical fields. The reconstruction method has good anti-noise performance and high reconstruction accuracy with the normalized root mean square error of less than 10% . The average calculation time of the simulation experiment is 31. 4 s, which can ensure the real-time performance of the acoustic measurement in the furnace. The proposed method of temperature and velocity fields simultaneous measurement can provide information to optimize the thermal fluid and combustion process in furnace.

Abstract:The harmonic error component under dynamic measurement is one of the main reasons that restricts the application of high precision and high resolution time-grating angular displacement sensor in the field of dynamic measurement. To address the problem of harmonic suppression in time-grating angular displacement sensor under dynamic measurement, the system model of time-grating angular displacement sensor is firstly briefly described. Secondly, the dynamic error mathematical model of the time-grating angular displacement sensor is formulated. Then, the mechanism of dynamic error of the sensor is explained, and the basic principle of adaptive Kalman filter (AKF) is elaborated the dynamic error suppression model of time-grating angular displacement sensor adapted to Kalman filter. The simulation results show that the dynamic error of the time-grating angular displacement sensor is reduced by about 70% after the adaptive Kalman filter under the condition of constant speed and variable speed, and with the increase of the sensor speed, the more obvious the suppression effect of harmonic error is. In the experimental application, the filtering algorithm has a good real-time prediction of the measured value of the time-grating angular displacement sensor, the sensor can run more quickly and stably, and the measurement error is reduced by about 80% at the speed of 100 r/ min. The results show that the adaptive Kalman filter has a significant role in suppressing the dynamic harmonic error of the time-grating angular displacement sensor, and can greatly improve the dynamic measurement accuracy of the sensor.

Abstract:A rapid detection of the position of the lateral stiffness change of towering structures in the time domain is proposed. Firstly, measurement points are arranged at equal height intervals on the same vertical line of the towering structure, and the synchronous dynamic response of each point in the horizontal direction is obtained. Then, the second-order statistical moment of the response signal is calculated, and the second-order statistical moment of the response of the adjacent measuring points is compared to draw the relationship curve of the ratio value with the height of the measurement point. Finally, according to the sudden change position of the curve, the position of the structural stiffness sudden change segment is detected. Based on the statistical moment theory of single-degree-of-freedom structures, the relationship between the statistical moment multi-degree-of-freedom structural systems and the lateral stiffness of structural segments is deduced. Combined with the matrix perturbation method, the feasibility of using the second-order statistical moment ratio curve of the structural response to detect the position of the structural segment sudden change of lateral stiffness is firstly proposed, and the applicability of the proposed method to analyze different towering structures under the influence of 30 and 40 dB noise and different excitation forms is demonstrated by using numerical model simulation. Finally, the measured response data of wind turbine towers in the field are analyzed and studied. The research shows that when the second-order moment of displacement is taken as the detection index, the position with abrupt stiffness change in the towering structure can be preliminary identified by the corresponding statistical moment ratio curve of the adjacent measuring points. There is no need to compare data indicators before and after sudden changes in lateral stiffness of towering structures, which helps to be applied in actual inspection projects of towering structures.

Abstract:To address the problem of negative vibration in the surface modification of cemented carbide by textured coating composite process, an analytical method based on the friction vibration behavior of textured coating surface is proposed to explore the modification effect of textured coating composite process. Therefore, the friction and wear test platform of micro textured AlSiTiN coated cemented carbide-titanium alloy grinding disc is established. Based on the short-time Fourier transform (STFT) and the gray algorithm, the regular mapping of friction vibration change and the stable period of vibration behavior are obtained. Then, the modification effect of microtexture AlSiTiN coating process parameters on cemented carbide is analyzed. Experimental results show that the micro texture and AlSiTiN coating have the most positive effect on the wear resistance of cemented carbide surface. During the stable period of 5~ 25 min from self-contact friction, the influence mechanism of micro-texture and AlSiTiN coating parameters on the surface modification of cemented carbide is obtained. The process parameters of the composite modification method to suppress the negative friction vibration of the cemented carbide surface provide a new idea for improving the surface performance of cemented carbide.

Abstract:To address the problems of large amount of data transmission and low efficiency when transmitting vibration data in mechanical vibration wireless sensor network of intelligent operation and maintenance, this article proposes a subband peak adaptive quantization fusion codec method. First, the edge device performed discrete cosine transform on the original data to ensure the energy concentration of the subbands. Then, the outliers in the sub-band DCT coefficients are extracted, and quantified by the subband peak adaptive quantization method to reduce the data distortion. Finally, byte fusion and bit fusion methods are used to concatenate and fuse different quantified data to reduce data redundancy. The proposed method is compared with other data compression methods to evaluate the performance. The experimental results show that the proposed method can effectively realize the fusion and compression of multi-sensor vibration data in mechanical vibration wireless sensor networks with limited channel resources. When eight sensors collect and transmit at the same time, the data compression ratio is 8. 335, the reconstructed signal to noise ratio is 20. 486 3 dB, and the transmission time is reduced by 37. 2% .

Abstract:To solve the problem of weak echo signal and low signal-to-noise ratio caused by large lift-off distance of electromagnetic ultrasonic thickness measurement transducer protection, which makes it difficult to directly and accurately extract transit time to obtain accurate thickness value in time domain, this article proposes an O-VMD transit time extraction method based on particle swarm optimization of variational modal decomposition parameters in frequency domain. The fixed parameters are selected for decomposition layers and penalty factors respectively, and the particle swarm optimization algorithm based on the joint fitness function of kurtosis and power spectrum entropy is used to obtain the ergodic optimization parameters of the variational mode decomposition. The VMD processing is performed twice to filter high-frequency and low-frequency noise. The maximum energy mode is selected for signal reconstruction, and the transit time of echo signal is obtained by applying Hilbert transform. Under different lift off distances, O-VMD, EMD and other methods are used for signal contrast processing of aluminum plate detection data with different thicknesses. The results show that the maximum error of O-VMD method is 0. 67% when the lift off distance is within 0 ~ 2. 1 mm, and the error is proportional to the lift off distance, providing a basis for accurately obtaining thickness measurement data with high lift off distance.

Abstract:To address the serious battery voltage fluctuation of the UAV power system, which leads to the large system noise and the low accuracy of identification results, this study proposes a kind of UAV power system parameters identification method based on the reverse predicted-extended Kalman filter. Firstly, the voltage-drop noise model is considered into the noise identification by establishing the extended parameter matrix. Secondly, the reverse predicted Kalman filter algorithm is proposed. An innovation square of threshold value is set. The ratio of the original predicted innovation square and the reverse predicted innovation square ratio is calculated, which adjusts the process noise by comparing the predicted innovation ratio with threshold size. In this way, the estimation model of correction is realized. Experimental results show that the average error of the RP-EKF algorithm is 39. 22 rpm, the root mean square error is 55. 85 rpm, and the mean relative bias is 0. 85% . Compared with the least square algorithm and the Kalman filter algorithm, the average error index values of the identification results using the proposed method of this study is improved by 41. 51% and 22. 26% , respectively. The root mean square error is improved by 49. 63% and 13. 0% , and the mean relative bias was improved by 41. 7% and 22. 7% . Results show that the proposed algorithm has higher identification accuracy than the traditional identification methods.

Abstract:To solve the problems of insufficient noise suppression ability and poor stability caused by the influence of environmental temperature and humidity, etc, a three-array ultrasonic wind measurement method based on the quadratic correlation algorithm is proposed. Firstly, a three-array wind measurement structure is designed by combining the principle of ultrasonic wind measurement, which consists of three transmitting and receiving integrated ultrasonic sensors. Secondly, a method for measuring ultrasonic propagation time based on quadratic correlation is given according to the structure of the system, which can effectively improve the accuracy of wind speed and direction measurement by using stronger performance of the quadratic correlation algorithm for noise suppression. It is theoretically explained that the proposed wind measurement method is not affected by the propagation speed of the ultrasonic wave itself ( i. e. , the environmental temperature and humidity). Finally, the effectiveness of the proposed method is verified by simulation experiments and a real measurement system is established. The practical test shows that the maximum relative error of wind speed measurement is 2. 0% , and the maximum error of wind direction angle measurement is 2. 1°. Results basically meet the accuracy requirements of ultrasonic wind speed and direction measurement.

Abstract:The 5G millimetre wave communication has attracted much attention due to its high carrier frequency and rate. It is a hot research topic for future mobile communications. However, in the design of millimetre-wave communication test instruments, multiple frequency multiplication is usually used to provide millimetre-wave fundamental oscillation for millimetre-wave base wave mixers, and the errors such as phase noise, carrier frequency offset and sampling clock offset additionally generated in this process can cause deterioration of the system demodulation index. To solve this problem, this article presents for the first time a method for comprehensive estimation of millimetre-wave errors based on the particle filtering algorithm, which can estimate the phase noise, carrier frequency offset and sampling clock offset in one go using the good robustness and adaptability of the particle filtering algorithm. Through simulation and experimental analysis, this article shows that the algorithm is more effective than the traditional PTRS phase noise estimation, and the EVM index is better. The proposed algorithm has been applied to the Chinese 5G millimetre wave base station synthesizer, and the EVM index can reach 2. 21% at a carrier frequency of 28 GHz, a bandwidth of 400 MHz and a modulation method of 64QAM.