Abstract:As a key component of the future aerospace vehicle power system, the condition monitoring and performance evaluation of the structure of composite tanks is one of the key issues to ensure the safe operation of spacecraft. Acoustic emission is a new dynamic non-destructive testing / monitoring technique that effectively monitors the structural performance of composite tanks. This paper takes composite tanks as the background. Firstly, the failure modes and common health assessment techniques of composite tanks are introduced. Secondly, the basic principles of acoustic emission detection technology are introduced, and the current status of research on the application of acoustic emission technology to the damage characteristics of composite tanks is reviewed. Finally, the development trends and challenges of acoustic emission monitoring of structural health of composite tanks are discussed.

Abstract:The basic error of electric energy metering equipment is greatly affected by environmental stress. And the relationship between multiple electrical stresses hard to be described under typical environmental stress. To address these issues, an improved particle swarm with long short-term memory network (IPSO-LSTM) is proposed to predict the basic error of electric energy metering equipment. Firstly, various stresses data in typical environment are normalized and data set allocation are preprocessed. To solve fluctuation trend of the error time series data, an extruded LSTM network architecture is established to analyze the variation trend characteristics of the error data. In this way, the nonlinear fitting ability of the model under multiple stress data is enhanced. Then, the improved PSO algorithm is used to optimize the model′s hyperparameters to reduce the influence of hyperparameters and improve the prediction performance of the model. In the experimental part, the proposed algorithm is evaluated and analyzed according to several electric energy metering equipment of one company. The environmental stress and error data are both considered by typical operating laboratories in Xinjiang region. The results show that the sample prediction accuracy indexes RMSE values reach 1. 08% and 1. 19% , respectively. And MAE values reach 0. 88% and 0. 96% , respectively.

Abstract:In this article, an active fault-tolerant control method based on the optimized adaptive threshold and fault reconstruction strategy is proposed for the nonlinear mechatronic system with uncertain parameters and sensor fault. Firstly, the linear fractional transformation form is used to model the nonlinear mechatronic system with parameter uncertainty. The optimized adaptive threshold based on the particle swarm optimization is established to improve the fault detection performance in the presence of parameter uncertainty. Secondly, the dynamic equations of the system are derived by the analytical redundancy relations, and the tracking control strategy of the healthy system based on the recursive terminal sliding mode is proposed to realize the tracking of load position. An adaptive sliding mode observer is formulated to reconstruct the sensor fault when the fault occurs in the system, based on which the adaptive active fault-tolerant control law is established. The switching of control law can be implemented online by using the fault detection result. Experimental results show that the proposed fault detection and active fault-tolerant control method can accurately achieve fault detection and fault-tolerant control of sensor within 0. 06 s, which evaluates the feasibility of the method.

Abstract:Aiming at the problem of low positioning accuracy to fault points in steel structures, an improved DV-Hop location algorithm is proposed, and a scheme of fault points detection based on the wireless sensor network technology is designed. This paper described the fault point location method in the steel structure building health monitoring system, analyzes the defects of the low node location accuracy of the traditional DV-Hop algorithm, and makes three targeted improvements. Firstly, four communication radiuses are adopted to refine the hops between nodes. Then, the weighted average hop distance is corrected by weighted processing. Finally, the improved sparrow search algorithm is used to locate the fault point. Taking the steel structure roof of the Terracotta Warriors and Horses Exhibition Hall No. 1 of Qin Shihuang Mausoleum as the simulation object, the MADIS_GEN software is used for modeling and dimensionality reduction. The improved ISSADV-Hop is compared with the traditional DV-Hop, IPSODV-Hop, and IGWODV-Hop algorithms in the fault point location of steel structure buildings. The results show that the normalized location errors are reduced by 19. 64% , 14. 87% and 8. 96% respectively, which verifies that the design scheme in this paper can effectively improve the positioning accuracy and is more suitable for fault point positioning in the steel structure health monitoring system.

Abstract:Triboelectric nanogenerator ( TENG) technology has been rapidly developed in the field of self-generation and intelligent sensing due to non-contact inductive measurement method. However, because of the material characteristics and environmental factors on the electrification process and charge transfer process between friction interfaces, it is difficult to achieve accurate control and modulation. Therefore, a gas-liquid intermittent triboelectric nanogenerator ( L-S TENG) detection technology is proposed to realize real-time monitoring of the types and physical characteristics of flow medium in PTFE tube. By analyzing the influence of environmental factors and structural parameters of the system, the mechanism and influence law of liquid-gas-solid three-phase in the contact electrification and induced electrical output process are revealed. It is found that the open circuit voltage increases significantly with the increase of the copper electrode width. With the width from 1 mm to 3 mm, the voltage increases by 1. 32 times. When the width increases to 6 mm, it increases by 1. 9 times. When the liquid temperature increases from 1℃ to 55℃ , the open circuit voltage increases firstly and then decreases. As the tube ages, the number of electrons transferred to PTFE tube decreases, the number of charge induced by copper electrode decreases, and the power conversion efficiency decreases. With the increase of humidity, the internal friction electric effect between the phase interfaces weakens, and the open circuit voltage decreases. Under laser action, it can effectively stimulate the energy level of carriers on the interface, so that the output performance and power conversion efficiency of the system are greatly improved.

Abstract:The N-type insulated gate bipolar transistor (N-IGBT) is widely used in various fields of modern industries due to its excellent performance. The prediction of the device degradations under specific conditions is of great significance for improving N-IGBT reliability. However, with the decrease of the N-IGBT process, the internal electric field intensity of the gate oxide is constantly increasing, and the degradation of the gate oxide caused by the positive bias temperature instability ( PBTI) is further intensified, the degradation is macroscopically reflected in the reduction of device remaining useful life (RUL) and changes of the threshold voltage. Based on the classical Power-Law model and the Arrhenius model, this article proposes a three-stage Power Law-Arrhenius comprehensive degradation model with relatively higher accuracy using the common parameter degradation time as the starting point. The degradation effect of positive bias temperature instability on N-IGBT through accelerated degradation experiment. Then, the threshold voltage which reflects the life of the power device after degradation is measured. Based on the genetic optimization algorithm and accelerated degradation experimental data, the comprehensive degradation model parameters are fitted and optimized, the mathematical expression form of the comprehensive degradation model is determined with an its accuracy above 85% , which is higher than that of the traditional power law model.

Abstract:The effective differentiation of pipe inner and outer wall defects is the premise of effective quantification of defects. A method of locating and distinguishing pipe inner and outer wall defects in high-speed magnetic flux leakage detection based on dynamic eddy current is proposed. In this method, the defect location is distinguished by the variation characteristics of magnetic field signals in inner and outer walls when the eddy current magnetic field and external magnetic field are coupled. Firstly, the mathematical model of highspeed magnetic flux leakage detection is established, and the eddy current distribution characteristics and the coupling law of eddy current magnetic field and external magnetic field are analyzed. By using the method of finite element analysis, the influence of coupling action law on the magnetization state of the inner and outer wall and the different characteristics of magnetic leakage signal of inner and outer wall defects at different positions are calculated. A high-speed magnetic flux leakage test platform is designed, and the effect of defect discrimination on the inner and outer wall of steel pipe at different running speeds and detection positions is studied experimentally. Results show that when the pipe enters the position of magnetized coil, the direction of the eddy current magnetic field is the same as that of the outer wall of the pipe. But it is opposite to that of the inner wall of the pipe. When the pipe leaves the position of the magnetized coil, the direction of the eddy current magnetic field is the same as that of the inner wall of the pipe, but opposite to that of the outer wall of the pipe. At different detection positions, the variation law of pipe wall magnetic field is obviously opposite, and with the increase of detection speed, the magnetization state is affected more obviously, and the more obvious the difference of magnetic leakage signals between inner and outer walls. High-speed detection can effectively locate and distinguish the defects of the inner andouter wall of the pipe. The experiment results and theoretical analysis have very good consistency

Abstract:To address the surveillance problem of micro unmanned aerial vehicle ( UAV) under low signal-to-noise ratio ( SNR) environment, this article proposes an integrated target tracking and detection method based on the sequential Monte Carlo track-beforedetect (SMC-TBD) algorithm by utilizing multiple input multiple output radar. Different from conventional methods considering detection and tracking processes independently, the proposed method relies on the raw unthresholding radar data cube after 3D FFT directly to calculate the accumulative existence probability of the target. In this way, the continuous detection and high precision tracking of micro UAV are achieved simultaneously. The novelty of the proposed method is that it can realize the target energy accumulation of time-rangeDoppler-azimuth domain by integrating the detection and tracking process. Therefore, the micro UAV surveillance performance under low SNR condition is improved. Experiment results show that the micro UAV tracking performance of the proposed method deteriorates gradually only when SNR is lower than - 20 dB, which can realize 8 dB improvement compared with radar measurements, extended Kalman filter and particle filter.

Abstract:Aiming at the problem that the uniformity of the uniform motion coordinate system is reduced due to the end effect of the planar magnetic field linear time-grid displacement sensor developed in the early stage, a method for suppressing the end effect of the planar coil is proposed, and an alternating magnetic field with higher uniformity is constructed. A new type of plane linear time grating displacement sensor that can suppress the end effect is developed. A mathematical model of planar coil excitation is formulated to analyze the influence of the end effect on the uniform magnetic field, and a double-layer complementary excitation coil structure is proposed to suppress the end effect. The dual-column excitation unit realizes the synthesis of travelling wave signals and verifies the effectiveness of the scheme through simulation. A simulation model to analyze the influence of the end effect on the measurement accuracy of the sensor is established, and the sensor parameters are optimized. Based on the PCB process, a new sensor prototype with a measuring range of 228 mm is fabricated and compared with the traditional sensor prototype. Experimental results show that the new planar linear time grating displacement sensor can effectively suppress the end effect of the sensor and improve the measurement accuracy. The intrapolar raw measurement accuracy is improved from ±20 μm to ±10 μm.

Abstract:The accurate thrust measurement has important application in the fields of satellite attitude control and gravitational wave detection, which has become a key issue limiting the development of thruster technology. Many related studies have been carried out at home and abroad. But, it is still difficult to balance heavy loads with high accuracy. In this article, we propose a measurement method based on parallelogram mechanism and build a thrust measurement device to address the problem of difficult thrust measurement of small thrust-to-weight ratio thrusters. It has advantages of high load carrying capacity, high accuracy and good stability. The parallelogram mechanism acts as both a thruster load-bearing component and an elastic element that converts the thrust into a single-degree-of-freedom linear displacement. The micro-displacement is measured by a laser interferometer. Then, the force value to be measured is calculated based on the Hooke′s law. The mechanical response of the device is tested by using electromagnetic force. Experimental results show that the minimum force value that can be resolved by the measurement system is 17. 2 μN with a range of 17. 2 ~ 2 789. 9 μN and a relative uncertainty of 1. 26% at an actual load-bearing capacity of 2. 5 kg. The method is applicable to the measurement of thrust and is of great importance to the development of thruster technology.

Abstract:A generalized Bouc-Wen (GBW) hysteresis model is proposed to accurately characterize the hysteresis nonlinearity of the piezoelectric actuator, since the classical Bouc-Wen hysteresis model cannot accurately characterize the inherent asymmetric frequencydependent dynamic hysteresis nonlinearity of piezoelectric actuators. Firstly, based on the classical Bouc-Wen hysteresis model, two asymmetric terms and a second-order IIR filter are introduced to characterize the asymmetric hysteresis and high-frequency phase hysteresis of the piezoelectric actuator, and further analyze the model parameter values with respect to the frequency variation law to determine the frequency-dependent parameters of the model. Then, the experimental platform of precision positioning of the piezoelectric actuator based on NI CompactRIO measurement and control system is built, and the parameters of the GBW model are identified by the particle swarm optimization algorithm and the proposed GBW model is evaluated experimentally. Experimental results show that the maximum error of the GBW model is 0. 190 6 μm and the root mean square error is 0. 043 1 μm for the variable frequency sinusoidal excitation signal, which is only 0. 65% of the displacement range of the piezoelectric actuator, with a decrease of 82. 07% and 62. 10% compared to the classical Bouc-Wen (CBW) model and the enhanced Bouc-Wen (EBW) model, respectively. Compared with the CBW model and the EBW model, the proposed GBW model significantly improves the model accuracy and broadband performance, and the existence of the analytical inverse model is easy for controller design, which helps to realize broadband and high-speed precision positioning of the piezoelectric actuator in ultra-precision instruments and equipments.

Abstract:The tooth profile form deviation of class-1 gear involute artefact is evaluated from roll path length 3 or 5 mm starting with the base circle according to the Chinese national standard for gear involute artefact. The arc length corresponding to the involute is only 0. 03~ 0. 18 mm, making the root of the involute tooth profile of class-1 gear involute is difficult to be measured. To exploit the accurate transmission of the value with class-1 gear involute artefact better, the special structure of class-1 gear involute artefact and the effect of the probe radius on the measurement results of the involute profile deviation is analyzed. The following conclusions are drawn. Firstly, the measurement error introduced by probe radius increases with increasing probe radius and decreasing rolling length as the rolling angle error at the root of involute is considered, and the measurement error near the base circle can reach 50% ~ 200% of the tooth profile deviation. Secondly as the error in the machining of the involute tooth surface is considered only, the measurement error introduced by probe radius and the affected range of rolling length increases with increasing probe radius and the base radius of the involute being measured, and the measurement error is about 10% ~ 60% of the profile form deviation within the range of 10% of roll path length at the tooth root. The conclusions above are verified by measuring the same gear involute artefact with probe radius rp = 0. 5 and 2. 5 mm. The basis for the ultra-precise manufacture, measurement and the selection of the roll path length to be used of class-1 gear involute artefact is provided.

Abstract:The MEMS IMU has the advantages of small size, lightweight, low cost, and high reliability. It is widely used in many fields such as robotics, virtual reality and smart wear. Low-cost MEMS inertial measurement units are affected by noise and zero-bias errors in practical deployment, hence testing and error compensation methods are required to improve their actual use accuracy. This article proposes a method that comprehensively tests and compensates for the error in the inertial measurement unit. Firstly, the error model of MEMS-IMU is established, and the deterministic parameters in the error model are calibrated by the optimization method. Secondly, the Allan variance analysis method is utilized to calibrate the random error parameters. Finally, the nonlinear optimization method fused with vision is used to estimate and compensate the zero bias online and in real-time, thereby achieving the goal of improving the navigation and positioning accuracy of the MEMS-IMU. Through experimental analysis, the above combined method does not need to use the specific test and calibration equipment, and can effectively compensate for the error of the low-cost MEMS inertial measurement unit and improve the positioning accuracy.

Abstract:A precision synthesis method of manipulator mechanism based on the optimal precision model is proposed. The genetic algorithm is used to optimize the tolerance allocation of D-H parameters, which provides a theoretical basis for the precision design of the manipulator. Taking a 7DOF cooperative manipulator based on the dualmotor servo drive joint as the research object, the geometric positioning accuracy of the manipulator is designed to be 1. 4 mm. The geometric positioning error model of the end-effector of the manipulator is established. The sensitivity analysis of parameter errors is implemented to find out the parameter errors which have a relatively great influence on the geometric position errors of the end-effector of the manipulator. According to the optimal precision mathematical model, the genetic algorithm is used to optimize the tolerance allocation of D-H parameters. After error simulation calculation and analysis, the maximum geometric positioning error of the manipulator is 1. 226 7 mm, with an average value of 0. 485 9 mm and variance of 0. 216 5 mm. This result meets the design requirements and provides a theoretical reference for the manufacturing and assembly of the manipulator. Compared with the precision synthesis method based on the minimum cost model, the precision synthesis method proposed in this paper does not need statistical manufacturing cost information and can ensure that the design precision of the manipulator meets the design requirements. It can be used for the precision design of single or small-batch manufacturing manipulators.

Abstract:Among the various methods to realize the self-propelled gun barrel orientation measurement, the total station measurement method has good comprehensive performance. However, the traditional methods of measuring barrel orientation with the total station have the problems of lack of north reference and axis simulation error. Therefore, a method based on a rotation matrix to measure the accurate orientation of the self-propelled artillery barrel with a total station is proposed. Then, the Euler-Rodrigues formula is used to deduce the deviation formula between the line connecting the marked points and the accurate axis orientation. In this way, the uncertainty model of the accurate orientation relative to each observation could be achieved. Then, to reduce the error of the measurement method, the optimal location of the total station is studied, and the optimal solution is implemented based on the principle of the Monte Carlo method. Finally, a simulated barrel installation experiment is carried out. Experimental results show that the measurement uncertainty under the optimal station layout scheme is within 0. 1, which evaluate the feasibility and accuracy of this method and suppressed the measurement error caused by the station layout scheme.

Abstract:As a main pollution gas, the emission of NO2 is endangering to the environment and human health, which should be monitored to achieve better governance. The existing imaging detection methods possess the advantages of a wide application range and good real-time performance, while accuracy and applicability are concerned in the reconstruction background. A method for quantitatively monitoring gas concentration using images of dual-channel target gas is proposed in this study. The NO2 concentration is retrieved from the ratio of 405 and 470 nm dual-channel light intensity, and the following theoretical and experimental research is carried out. Specifically, the relationship between gas column concentration and dual-channel light intensity ratio is obtained according to theoretical derivation. The effect of the dual-channel exposure time on the calibration equation is analyzed. The collected dual-channel light intensity ratio is compared with the theoretical value, and the difference between them is 0. 26% . The optimal value of dual-channel light intensity ratio under different solar zenith angles is measured by collecting the solar scattered radiation spectra at 26. 08° north latitude under various meteorological conditions. The performance of the detection camera is analyzed, and the detection range is 19. 6 ppm m. Concentration calibration and retrieval experiments give a calibration function, retrieve the two-dimensional distribution of gas concentration in diffusion, and validate the reliability of the dual-channel spectral imaging method for quantitative detection of gas concentration.

Abstract:Electrical tomography is a kind of non-destructive testing technique to image the conductivity distribution within the observation domain. The finite element method is commonly used to solve the inverse problem. The size of the mesh elements can affect the accuracy of the approximation method. The finer size is usually utilized to improve the spatial resolution of the reconstructed image. However, the computational cost will be increased, which makes the inverse problem more underdetermined since the number of unknowns is increased. To address this issue, an adaptive mesh generation method based on the image gradient is proposed to optimize mesh generation to improve the reconstructed accuracy on the premise of not significantly increasing ill-condition. According to the gradient of the initial reconstructed image, the proposed method optimizes the subdivision of the observation field by adaptively improving the mesh density of the inclusion region and reducing the mesh density of other regions. The commonly used mesh generation methods are used to compare with the proposed method. Simulation and experiments show that the reconstructed image error is reduced by 15% on average and the correlation coefficient is increased by 7% on average. Results show that the proposed mesh generation method can improve the reconstruction accuracy of inclusions and the image reconstruction quality, and reduce the calculation error without increasing the number of grids.

Abstract:Aiming at the problem that the shield guided laser spot cannot be accurately recognized due to the interference of stray light in the construction site. To address this issue, an anti stray light algorithm based on the digital image processing is proposed, which utilizes the pulse characteristics of guided laser. Firstly, the relationship between the exposure time of the industrial camera and the laser pulse period is analyzed. Two images before and after the guided laser pulse can be effectively acquired in the stray light environment by adjusting the exposure time of the industrial camera. Then, the difference of two frames of images to obtain the target spot. Finally, the appropriate structural element is used to corrode the residual shadow in the image to completely eliminate the adverse effects of stray light. Experimental results show that the recognition accuracy of guided laser spot is better than 93. 75% by using the anti stray light algorithm within the applicable distance of laser target. Compared with the other anti stray light algorithm, the recognition accuracy is improved by 21. 87% , 23. 13% , and 26. 87% , respectively in short, medium and long distance, which can meet the requirements of shield guided construction and has a good application prospect.

Abstract:The cementing mud flowmeter is an instrument that is used to measure mud flow rate in oilfield cementing engineering. It belongs to tangential turbine flowmeter. To explore the influence mechanism of fluid conditions on its metering characteristics, the mathematical models of the driving moment and the resistance moment of the impeller of the flow meter are firstly formulated. Based on this, the instrument coefficient K model is established. And the fluid viscosity is confirmed to be one of the influencing factors. Secondly, in actual cementing operation, the influence of viscosity on meter measurement characteristics is complicated. Therefore, the finite element analysis software is used to establish the 6DOF impeller passive rotating fluid simulation calculation model. The flow field characteristics and instrument coefficient characteristics under the conditions of various fluid viscosity 35, 45, 55, 65, 75 mPa·s are simulated and analyzed. And the influence law of viscosity change on the flow meter measurement characteristics is summarized. Finally, the average error is 1. 38% by comparing the actual cementing measurement data with the simulation data, which evaluates the effectiveness of the simulation model.

Abstract:Aiming at the problem that the current three-axis gyroscope calibration relies on expensive turntable equipment or the calibration parameters are incomplete, a method based on a two-step correction method is proposed. Firstly, the six-position method is adopted to calibrate and compensate the 12-parameter model of the accelerometer, the scale factor of the triaxial gyroscope, and the static bias of the three-axis gyroscope. Then, the non-orthogonal error model of the triaxial gyroscope is formulated for the system-level calibration. The two-step correction method can quickly and accurately identify various errors without precision equipment, and obtain a good calibration effect. Simulation experiments show that the average non-orthogonal error obtained by this algorithm is close to 1% , the standard deviation is less than 0. 1% , the average scale factor error is less than 0. 14% , and the standard deviation is less than 0. 004% . The actual experiment shows that in the attitude update results of 65 s pure inertial navigation, the pitch angle error and the roll angle error of this calibration method can reach 0. 624° and 0. 67°.

Abstract:An arched sensitized microfiber magnetic field sensor with temperature compensation based on TbDyFe is proposed. The magnetic field sensor is consisted of FBG, an arched microfiber, and a TbDyFe. Microfiber is bonded to the TbDyFe by UV glue. Compared with the non-arched microfiber, the arched microfiber can convert the elongation of TbDyFe into the change of curvature radius of microfiber, resulting in the shift of interference wavelength, thereby realizing the improvement of the sensitivity. The interference wavelength of microfiber shows a blue shift with the increase of magnetic field intensity. The magnetic field sensitivity is 47. 81 pm/ mT and FBG is not sensitive to the magnetic field. The magnetic field sensitivity of arched microfiber is 11. 66 times higher than that of the non-arched microfiber. During the heating process, the interference wavelength of arched microfiber is blue-shifted and the temperature sensitivity is 43. 02 pm/ ℃ . The interference wavelength of FBG is red shifted and the temperature sensitivity is 9. 34 pm/ ℃ . The magnetic field sensor shows good repeatability and linearity with the increase of the magnetic field. The cascaded FBG is not sensitive to the magnetic field and can realize temperature compensation for the sensor.

Abstract:In view of the problems that the current tactile sensors applied to electronic skin cannot have flexibility and multi-modal information perception, a finite element simulation and experimental study of the material recognition function of two fiber Bragg grating (FBG) tactile sensors encapsulated in the same polymer sensing unit is carried out. Firstly, the principle of the FBG tactile sensor and the mechanism of material recognition of the contact object based on thermal transfer are derived; then, the thermodynamic simulation analytical experiments of the encapsulated material with different contact objects are carried out; finally, the experimental system platform is built and the material recognition of FBG flexible tactile sensor is investigated experimentally. The simulation and experimental results show that when the contact object is aluminum, iron and plastic at 70℃ respectively, the maximum values of the central wavelength shift of the FBG temperature sensor due to thermal transfer are: ΔλB1 = 0. 588 9 nm, ΔλB2 = 0. 277 3 nm and ΔλB3 = 0. 169 2 nm, and the rate of change of the central wavelength shift with time in the first 10 seconds of exposure are k1 = 31 pm/ s、k2 = 19 pm/ s and k3 = 6 pm/ s. Expanding the recognition function of the contact object material of the FBG tactile sensor can realize the perception of more modal information of the electronic skin, which has certain application value.

Abstract:Borehole pressure relief is the primary measure to control rock bursts in high in-situ stress mines. Accurate measurement of drilling tool attitude of the drilling robot for rockburst prevention is the premise to ensure the drilling hole position and pressure relief effect. Therefore, this article proposes a drilling tool attitude calculation method based on inertial sensing assembly and BP neural network. By designing the spatial array layout of inertial sensing assembly (spatial array IMU), the data fusion model and the attitude calculation model of spatial array IMU are formulated, which could realize the high-precision calculation results of drilling tool attitude. On this basis, the error compensation method of inertial sensing units based on the BP neural network is proposed and the error compensation model of drilling tool attitude calculation is established. The feasibility of spatial array IMUs calculation and error compensation method is evaluated by analyzing the drilling tool simulation motion. Finally, the drilling tool attitude monitoring experimental platform of the drilling robot is established to compare and analyze the drilling tool calculation results of different methods. Experimental results show that after the error compensation of the BP neural network model, the attitude accuracy of the drilling tool calculated by the proposed method is significantly improved, and the average errors of azimuth, inclination, and roll angle are 0. 099°, 0. 079°, and 0. 045°, respectively. The compensation measures effectively restrain the drift and error accumulation of inertial sensing units, and there is no divergence in the error curve of drilling tool attitude calculation. Therefore, this method can continuously and reliably monitor the drilling tool attitude of drilling robot for rockburst prevention s and has high popularization and application value.

Abstract:To improve the accuracy and robustness of the speaker tracking system in noisy and reverberant environments, an adaptive unscented particle filter (AUPF) algorithm based on multi-feature is proposed. The multi-feature of the speech signal is regarded as the observation information in this algorithm, where the multi-hypothesis and frequency selection function is applied to the mechanisms of time delay selection and beam output energy optimization. Subsequently, the likelihood function is constructed by combining these two mechanisms, which makes up for the deficiency that noise and reverberation cannot be restrained simultaneously by a single feature. Considering the randomness of speaker motion, a new proposal distribution is utilized in the particle filter algorithm, which combines the unscented Kalman filter (UKF) and the robust estimation theory based on the adaptive constant speed model to improve the adaptability of the model. The simulation and experimental results show that based on AUPF, the position average RMSE of multi feature algorithm is reduced by more than 18% compared with that of SBFSRP, and under multi-feature observation, the position average RMSE of AUPF algorithm is reduced by more than 14% compared with that of CV algorithm. It has the characteristics of high tracking accuracy and strong numerical stability.

Abstract:The low signal-to-noise ratio is a major challenge for ultrasonic inspection of coarse crystal structures, which is caused by the large amount of scattering noise generated by coarse grains. To overcome the insufficient of the traditional signal denoising method in waveform distortion and amplitude attenuation, an overlapping group sparse variational method based on the non-convex penalty function is proposed for ultrasonic signals denoising. Based on the typical ultrasonic signal containing scattered noise, the influence of the main parameters of the sparse variational method for overlapping groups of nonconvex variables ( such as the type of function of nonconvex variables, regularization parameters and multiplication factors) on its noise suppression effectiveness is analyzed, and the basis for determination of suitable parameters in processing of ultrasonic signals is determined. On this basis, the overlapping group sparse variational method is applied to the noise suppression of ultrasonic signals detected from steel ingot. Results show that the method can effectively suppress the scattering noise in ultrasonic signals detected from steel ingot and improve the signal-to-noise ratio of ultrasonic imaging by more than 6 dB. The research work is a useful exploration for ultrasonic detection of coarse crystalline materials.

Abstract:The accuracy of the direction of arrival (DOA) estimation algorithm and the resolution are limited by the number of channels. To address these issues, this article proposes a meshless DOA estimation algorithm based on channel compression-atomic norm minimization (CC-ANM). First, the algorithm compresses the number of channels. Then, the eigenvalue decomposition is performed on the covariance matrix of the compressed data. The decomposed eigenvalues and eigenvectors are used to construct a new observation vector to solve the ANM problem under the single snapshot model. Finally, the Toeplitz matrix is established according to the optimal solution of the positive SDP problem. The DOA parameter estimation result of the signal is achieved through its Vandermonde decomposition. Simulation experiments show that the CC-ANM algorithm can achieve an estimation accuracy below 0. 1° when the number of array elements is 20, the compression rate is 2, the SNR is 20 dB, and the number of snapshots is 200. The 100% measurement is possible for signals with an angular separation of more than 2°. The test data received by the instrument with an incident angle of 0° show that the estimation accuracy of the algorithm is below 0. 3°, which is better than the compressed sensing algorithm under the same condition.

Abstract:The time constant of the thermocouple is a key parameter of its dynamic characteristics. Obtaining temperature step by laser excitation is the main way to measure the time constant of the high-speed thermocouple. The heat transfer process of thermocouple excited by positive and negative step laser is compared and analyzed in this article. It is pointed out that the negative step is more consistent with the theory of time constant. The response model of thermocouple in the negative step of step modulated laser and pulse modulated laser is formulated. It shows that the pulsed laser can effectively solve the problems existing in experimental results of the step laser. The time constants measured under the same conditions are 73. 78 and 41. 34 ms, respectively. The limit performance of thermocouple response can be obtained by pulse laser test. Experimental results also show that the pulse energy has little effect on the measurement results of the time constant. Smaller thermocouples respond faster. The forced convection has a great influence on the measurement results of the thermocouple time constant.

Abstract:The choice of primary Lamb wave mode and the determination of excitation conditions play important roles in the nonlinear Lamb wave technology. The excitation window of the second-harmonic Lamb wave is defined by accumulation distance when the phase velocity is approximate matching. The strictness of the primary Lamb wave excitation condition is discussed. The excitation efficiency of the second-harmonic Lamb wave is evaluated by the amplitude of surface displacement. The influence of phase velocity approximate matching on the excitation efficiency as well as the excitation efficiency of different modes of Lamb wave is discussed. The theoretical results show that, within the accumulation distance, the increase of the propagation distance could improve the excitation efficiency of the second harmonic. But, the harmonic generation conditions are more strictly. A certain degree of phase velocity approximate matching will improve the excitation efficiency of second-harmonic Lamb wave. For different primary wave modes, the excitation efficiency and the strictness of the excitation condition of second-harmonic Lamb wave are different. The excitation window and the relative nonlinear coefficient of the longitudinal S2 / S4 mode at 90 and 150 mm propagation distance, as well as of longitudinal S1 / S2 and S2 / S4 mode at 150 mm propagation distance, are measured and compared. The measurement results are consistent with the theoretical analysis. In this article, the nonlinear effect of the Lamb wave in the case of approximate matching of phase velocity is discussed, which provides the analysis method and basis for the practical application of the Lamb wave.

Abstract:In view of the nonlinear industrial data disturbed by strong noise, a novel operating performance assessment method based on the stacked supervised denoising auto-encoders ( SSDAE) is proposed for complex industrial process. Firstly, a supervised denoising auto-encoder (SDAE) model is formulated, in which the performance grade labels are introduced to train the model. In this way, the SDAE can learn the characteristics closely related to the process operating performance and has strong ability to distinguish performance grades. Secondly, the SSDAE model is established by the stacking multiple SDAE model layer by layer and used to extract deep features which are closely related to the operating performance from the process data. Then, the deep features are used as the inputs of the SoftMax classifier. And the operating performance assessment model is achieved. Finally, the proposed method is applied to the hydrometallurgical process. Simulation results show that the assessment accuracy of SSDAE is up to 95% after the data are damaged by randomly setting zero in the proportion of 30% , which is obviously superior to other compared methods. Hence, the good performance and feasibility of the proposed method are verified under the condition of strong noise interference.

Abstract:To plan a more energy-efficient picking path, an artificial bee colony-adaptive genetic algorithm for warehouse robots is proposed. The performance of the basic genetic algorithm is considered, which depends on the quality of the initial population, the selection, crossover, and mutation operations. Firstly, the artificial bee colony algorithm is used to initialize the initial population, which can enhance the diversity of the population. The path length, turn times, and robot running energy consumption are taken as the evaluation indexes of the fitness function. Then, on the basis of crossover and mutation operators designed by adaptive strategic adjustable trigonometric functions, it can improve the convergence speed of the algorithm. Simulation results show that the path energy consumption of the artificial bee colony-adaptive genetic algorithm proposed in this article is 5. 22% lower than that of the basic genetic algorithm in the 20×20 grid map. On the 40×40 grid map, the energy consumption of the path planned by the artificial bee colonyadaptive genetic algorithm proposed in this article is 9. 08% less than that of the basic genetic algorithm. Finally, experimental results show that the energy consumption of the artificial bee colony-adaptive genetic algorithm is reduced by 7. 64% , and the planned path is smoother, which is more suitable for the path planning of warehouse robots.

Abstract:Unmanned vehicles usually locate themselves based on prior map matching when operating autonomously in industrial scenarios. However, the scene change will affect the positioning accuracy of unmanned vehicles. In view of this, we propose a LiDAR robust positioning and map maintenance architecture for changing scenarios, which includes map matching, positioning optimization, and map maintenance modules. A matching algorithm based on change detection is proposed, which reduces the matching error caused by changing scenarios. A factor graph fusion mode based on LiDAR odometer and prior map matching is designed to improve the robustness of the positioning solution. A filtering method of false detection points based on nearest point search is proposed, which improves the accuracy of change point detection. Finally, we establish a changing scene verification environment through simulation and experimentation and compare the performance of matching based on Loam and the proposed algorithm. The results show that the algorithm can effectively suppress the matching error caused by the scene change, the root mean square error of positioning is better than 3 cm in the actual scenario, and the positioning accuracy is improved by 67. 4% compared with the traditional algorithm.

Abstract:Discrete acoustic array arranged in a certain geometric structure takes advantages of energy concentration, adjustable radiation direction, and flexible configuration. An array design and optimization method is proposed to solve the difficulty of controlling orientation direction and backward radiation suppression when the acoustic array radiates high-intensity low-frequency sound waves. Firstly, the horizontally arranged linear array is used to limit the width of the main beam, and the design principle of directivity is analyzed. Then, the vertical position and phase of the multi-layer linear array are controlled, thereby achieving the suppression of backward radiation. Finally, an improved genetic simulated annealing algorithm is proposed to optimize the lateral coordinate of the array element and further improve the performance of the array. Simulation and sound field test results show that the design method can effectively control the directivity and backward radiation level of the array. The test results are consistent with the theoretical analysis. When the designed depth array emits 100 Hz sound waves, the half-power angle is 21. 91°. The average radiation suppression ratio in the direction from 50° to 60° is 8. 82 dB and the radiation suppression ratio in the direction from 90° to 180° exceeds 20 dB.