Table of Content

25 May 2020, Volume 48 Issue 5

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Architecture & Civil Engineering

Experimental Study on Mechanical Behaviors of Cement Mortar Containing Excavated Soil



WU Bo, CAO Huixuan, LIN Lang, et al

2020, 48(5):  1-8.  doi:10.12141/j.issn.1000-565X.190880

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The treatment approaches for weathered residual soil of granite and alluvial-diluvial，which are the most widespread excavated soils in South China，were put forward． After the processing procedures，the usable excava-ted soils were utilized to partially or fully replace the river sand to prepare cement mortar，and the water-reducing admixture demand for suitable working performance of the cement mortar was investigated． The compressive and flexural tensile tests were carried out to examine the influence of the replacement ratio of excavated soil on the me-chanical behavior of cement mortar containing excavated soil． The results show that: (1) on the premise of ensu-ring good working performance of the cement mortar，water-reducing admixture demand increases with the increase of the replacement ratio of excavated soil，but its largest dosage (calculated by solid content) accounts for only 1. 1% of the binding material; (2) the compressive strength，flexural tensile strength and elastic modulus of the
cement mortar prepared partially or fully with the usable content of alluvial-diluvial soil are roughly equivalent to those of the cement mortar containing no alluvial-diluvial soil，so it is practicable to fully replace the river sand with the usable content of alluvial-diluvial soil in actual practice; (3) replacing 30% of the river sand with the us-able content of weathered residual soil of granite has no significant adverse effects on the mechanical behaviors of the cement mortar，but when the replacement ratio increases to 50%，the 28d flexural tensile strength，compres-sive strength and elastic modulus of the cement mortar maximally drop by 6%，15% and 10%，respectively，compared with those of the cement mortar without weathered residual soil of granite． It is suggested that the re-placement ratio of such soil should not exceed 50% in practice．


Study on Acoustic Condition of Primary and Secondary School Classrooms in Subtropical Region of China 



LI Nan ZHAO Yuezhe WU Shuoxian

2020, 48(5):  9-14,40.  doi:10.12141/j.issn.1000-565X.190787

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A survey on the acoustic condition of 14 primary and secondary school classrooms in subtropical region was carried out． Room acoustic parameters，total sound level during teaching periods，tearcher's sound level and occupied noise level were measured to evaluate the acoustic environment of primary and secondary school class-rooms． The result shows that unoccupied acoustic parameters is significantly related to building parameters，and unoccupied acoustic conditions affect the noise levels during teaching periods． To get good speech intelligibility，the volume per seat needs to be controlled when building the classroom．


Joint Calculation of OpenSees and LS-DYNA Based on Numerical Substructure Method



ZHANG Ning ZHANG Deyu GU Quan

2020, 48(5):  15-21.  doi:10.12141/j.issn.1000-565X.190311

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The analysis of frame structure under impact often brings great difficulties to numerical simulation due to the contradiction between large volume and small impact surface． The failure of frame structure is often caused by the break down of a key component，while the whole structure is still in an elastic state． So it's unnecessary to a-dopt a unified non-linear model in the simulation． In order to deal with this problem，the Numerical Substructure Method (NSM) was adopted to isolate and precisely simulate the components which are in non-linear state． Thus the impact problem of large volume frame structure was transformed into the problem of linear elastic analysis of the main structure and nonlinear analysis of the substructure． Based on NSM，a joint calculation method of OpenSees and LS-DYNA was put forward and implemented． And the method was used to study and analyze the role of ECC material in impact simulation，and to verify the feasibility of the joint calculation method and the superiority of ECC material．


Classification Method of Member Importance Based on Strain Energy Theory for Lattice Shell Structure 



LI Yunsong, NIE Qi, LUO Yongfeng, et al

2020, 48(5):  22-31.  doi:10.12141/j.issn.1000-565X.190547

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The traditional classification methods of member importance are often exclusively applied to linear-elas-tic structures，and they are not suitable for latticed structure with strong nonlinear effect． Meanwhile，these classi-fication methods also have limitations． To solve this problem，a classification method of member importance based on strain energy was proposed for latticed structure． Based on strain energy theory，the concept of total strain ener-gy at critical point was introduced． Taking total strain energy at critical point as the evaluation index，the influence of local member's break down on the load-carrying capability of whole structure was analyzed． Thus each member's importance was figured out． Ｒeduction coefficients of total strain energy at critical point were considered as indexes of member importance． According to present principles of member importance classification，and based on K-me-doids classification method，a classification method of member importance with non-fixed boundary was proposed．The analysis results of Kiewitt lattice shells show that the classification boundary of member importance should not be fixed to a certain value． The number and location of important members vary in different failure cases，so they should be determined based on actual information． Method proposed in the paper can provide more information
than the design stress ratio method in detecting important members in structure． Classification method of member importance based on alternative path method should not be used for the normal inspection and appraisal of struc-tures．


Traffic & Transportation Engineering

Vehicle Lane-Change Trajectory Prediction Model Based on Generative Adversarial Networks 



WEN Huiying ZHANG Weigang ZHAO Sheng

2020, 48(5):  32-40.  doi:10.12141/j.issn.1000-565X.190182

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The prediction of vehicle trajectory has great significance in the autonomous vehicles and internet of ve-hicles systems． Vehicle trajectory prediction can help to judge the future motion state of vehicles and to avoid colli-sion． Therefore，a vehicle lane-change trajectory prediction model based on generative adversarial networks was suggested． Vehicle lane-changing data was collected with High-precision GPS instruments through complete vehicle test in urban highways． On this basis，a trajectory prediction model based on the generative adversarial networks was established． The generator of GAN adopts the LSTM encoder-decoder structure，and the future lane-changing trajectory is generated through the decoder by inputting the given observed lane-changing trajectories． By construc-ting neural network based on the MLP，the discriminative model can distinguish the generated trajectory and the target trajectory through multiple discriminating methods． By jointly training generative model and discriminative model，the future trajectory of single vehicle in real time can be predicted． Through cross-validation and model
comparison，the effects of historical trajectories and prediction trajectories of different lengths on prediction accura-cy were analyzed，and the validity and accuracy of the model was verified． The results show that，compared with the traditional model，our model can predict the lane-change trajectory over a long period of time with an obviously improved accuracy．


Equality-Efficiency Balance-Oriented Optimization of Long-Short Route Strategy in Urban Rail Transit 



YAO Enjian ZHANG Jinmeng HUAN Ning

2020, 48(5):  41-48,57.  doi:10.12141/j.issn.1000-565X.190799

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Train schedule serves as a foundation for operations management in urban rail transit (UＲT)． Aiming at releasing local congestion caused by demand surge，balancing passengers' travel delays and improving the overall efficiency of the whole network during the rush hour，an equality-efficiency balanced method for optimizing long-short route strategy in UＲT system was proposed． First，passengers were divided into specific categories according to their trip characteristics． Then the operational cost of UＲT company and the travel cost of passengers could be measured precisely． Next，an optimization model that strikes a good balance between maximizing transport capaci-ty and minimizing passengers' travel delays was formulated． To verify the effectiveness of proposed model，an em-pirical analysis was then presented． The results show that，when adopting a long-short route strategy for morning peak，the short route should cover the sections with maximum load rates in both up and down directions． The utili-zation rate of transport capacity is significantly affected by the length of short route． The train marshalling scheme should consider the maximum of section load and its threshold need． With the optimized long-short route strategy，
the utilization rate of transport capacity rises by 16. 69%，and the operational cost of UＲT company decreases by 21. 11%． In addition，passengers' travel delays also reach a well-balanced status．


Effects of Hydrophobic Nano-Silica on the Low-Temperature Performance of Asphalt Binder



DAI Wenting, AN Yin, HAO Ruyi, et al

2020, 48(5):  49-57.  doi:10.12141/j.issn.1000-565X.190717

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The low-temperature performances of 90# asphalt，nano-silica modified asphalt and hydrophobic nano-silica modified asphalt were comparatively evaluated with low-temperature performance test of conventional asphalt and bending test of small mortar beam in order to investigate the effect of the hydrophobic nano-silica on the low-temperature performance of asphalt binder． Scanning electron microscope test were conducted to analyze the chara-cteristics and modification mechanism of the two kind of modified materials． Then the Fourier transform infrared spectroscopy test was conducted to study the function mechanism of modified asphalt to improve low-temperature performance of asphalt． Ｒesearch results show that: the penetration index of hydrophobic nano-silica modified as-phalt is the highest; its equivalent brittle point is 80% lower than that of nano-silica modified asphalt; its maxi-mum flexure tensile strain is 80% higher than that of nano-silica modified asphalt and 350% higher than that of ma-trix asphalt at －15℃; its ultimate flexural tensile strength is 69% higher than that of matrix asphalt at －15℃，which indicates that the low temperature performance of hydrophobic nano-silica modified asphalt is excellent． Hy-drophobic nano-silica particle is 11% smaller than nano-silica particle，and the size distribution of hydrophobic nano-silica particle is more uniform． The surface of hydrophobic nano-silica particle is organic． Compared with nano-silica particle，the surface of hydrophobic nano-silica particle is rougher． Hydrophobic nano-silica particle is not easy to gather when modified mixing． The three-dimensional mesh structure formed by modified particles and asphalt improves the low-temperature characteristics of asphalt． The C—O chemical bond is formed between hydro-phobic nano-silica and asphalt，which enhances the bond between modified particles and asphalt，and the strong chemical bond shortens the length of asphalt tensile chain which results in an increase in the deformation ability．


Estimation of Comprehensive Impact of External Factors on Interlayer Fatigue Life of Asphalt Pavement Based on ISS & SSDR



AI Changfa, HUANG Yangquan, LUO Liufen, et al

2020, 48(5):  58-66,74.  doi:10.12141/j.issn.1000-565X.190501

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The evaluation of interlayer fatigue performance of asphalt pavement is highly dependent on fatigue life．But the factors considered in the existing interlayer fatigue life prediction model are not comprehensive enough，and there is no correlation between the interlayer fatigue life prediction model and the initial shear stiffness． In this study，four-point shear fatigue tests under four external factors (i． e． shear stress amplitude，temperature，loading frequency，normal stress) were carried out and Initial Shear Stiffness (ISS) and Shear Stiffness Decay Rate (SSDR) of interlayer performance were obtained． Nonlinear multiple regression models for ISS and SSDR were established，respectively． And an interlayer fatigue life N f prediction model was constructed based on ISS and SSDR． The results show that: (1) the influence degree of four external factors on the interlayers ISS ranks: tem-perature ＞ shear stress amplitude ＞ loading frequency ＞ normal stress; the influence degree of four external factors on the decay rate of interlayer shear stiffness ranks: normal stress ＞ temperature ＞ shear stress amplitude ＞loading frequency; the influence degree of four external factors on interlayer fatigue life ranks: temperature ＞ nor-mal stress ＞ shear stress amplitude ＞ loading frequency; (2) the interlayer fatigue life N f prediction model based on ISS and SSDR realizes the correlation among the three indexes of the interlayer fatigue life N f ，ISS and SSDR． The research results provide a new way for the prediction of interlayer fatigue life and a theoretical support for strengthe-ning interlayer design．


Electronics, Communication & Automation Technology

A New Kind of Ring Oscillator Structure



YAO Ruohe WANG Xiaoting

2020, 48(5):  67-74.  doi:10.12141/j.issn.1000-565X.190673

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A differential delay cell with noise cancellation structure was proposed in order to reduce the phase noise of ring oscillators． The delay cell consists of main path，auxiliary path and active feedback． The main noise source of the delay cell can produce fully correlated in-phase noise voltages at the differential outputs． When the noise cancellation condition is met，the noise voltages can be cancelled，thus the noise voltage at the differential outputs is reduced． The delay cell provides an additional phase shift by introducing a mirror pole，which can be employed in a general architecture of a two-stage differential ring oscillator with quadrature output，effectively reducing the clock jitter and the phase noise of the ring oscillator． The proposed ring oscillator was designed and simulated with 0. 18 μm TSMC CMOS technology under 1. 8 V． The results show that the center frequency of the oscillator is 800 MHz and the phase noise is －117. 5 dBc/Hz at 1 MHz offset，which is only 1. 01 dBc/Hz from the theoretical calculation result．


Parameter Estimation of 2D-GTD Model Based on the Improved 2D-ESPRIT Algorithm 



ZHANG Xiaokuan, ZHENG Shuyu, ZHAO Weichen, et al

2020, 48(5):  75-81,91.  doi:10.12141/j.issn.1000-565X.190643

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The classical 2D-ESPRIT algorithm is sensitive to signal-to-noise-ratio (SNR) when estimating the pa-rameters of two dimensional (2D) geometric theory of diffraction (GTD) model． To solve the problem，an im-proved 2D-ESPRIT algorithm，which improves the anti-noise performance and parameter estimation performance ef-fectively，was proposed． Firstly，the improved algorithm obtains a new matrix Y containing the conjugate informa-tion of the original matrix Ee by constructing an exchange matrix． Secondly，a new covariance matrix R can be ob-tained by auto-correlation，cross correlation，superposition and average processing． Finally，the parameters of 2D-GTD model can be estimated by calculating the new covariance matrix R． Simulation results show that the im-proved 2D-ESPＲIT algorithm has a better anti-noise performance，and it owns higher estimation precision and more stable performance than the classical 2D-ESPRIT algorithm accurately in the case of low signal-to-noise ratio． The impact of other factors，such as matrix pencil parameters and paring variable β，on parameter estimation precision
was also studied，which can be provide references for future simulations．


Multistage Image Compressive Sensing Neural Network Based on Residual Learning 



YANG Chunling PEI Hanqi

2020, 48(5):  82-91.  doi:10.12141/j.issn.1000-565X.190312

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There are two main problems in traditional Image Compressive Sensing (ICS): in sampling aspect，traditional linear sampling methods have some limitations; in reconstruction aspect，optimization-based reconstruc-tion methods are highly time-consuming． Newly proposed ICS Neural Network can successfully deal with the speed problem in reconstruction，but lacks the accuracy of traditional algorithms． To solve this problem，a novel multi-stage ICS network based on residual learning (MSResICS) was proposed． It consists of three sub-networks，namely，sampling sub-network，initial reconstruction sub-network，and image enhancement sub-network． In sampling stage，with the help of residual learning，a nonlinear sampling sub-network was designed，which breaks the limitation of conventional sampling method and retains richer image information in samples． In reconstruction stage，the initial reconstruction sub-network extracts features from samples and obtain an initial reconstructed image of high quality by introducing interpolation convolution． With residual learning and interpolation convolution，a mul-tistage image enhancing sub-network was proposed to further refine the reconstruction image and improve the quality of final result． Extensive simulations show that MSResICS has a better reconstruction accuracy than the existing opti-mal ICS reconstruction methods．


Froth Collapse Rate Detection by the Fusion of FＲEAK and Omnidirectional Similarity in NSST Domain 



LIAO Yipeng, ZHANG Jin, CHEN Shiyuan, et al

2020, 48(5):  92-101.  doi:10.12141/j.issn.1000-565X.190538

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A new froth collapse rate detection method by the fusion of fast retina keypoint (FREAK) and shape omnidirectional similarity in Nonsubsampled Shearlet transform (NSST) multiscale domain was proposed，consi-dering the difficulty to detect the froth collapse rate resulted from continuous flow and movement deformation． First-ly，two adjacent froth images were decomposed through NSST，froth bright spots are extracted by segmentation of low frequency subband image． And feature points were tested by direction modulus maxima detection and nonmaxi-mum suppression among multiscale high frequency subbands，then FREAK sampling pattern was improved and used for feature points description and matching． Secondly，potential collapsed bubbles were extracted according to the number of matching points that around the bright spots of previous frame，and then collapsed bubbles were selected from potential collapsed bubbles by using shape complexity feature and omnidirectional similarity detection
of bright spots between previous frame and next frame． Finally，the bubble collapse rate was calculated according to the detection results of collapsed bubble． Experimental results show that，the proposed method is affected little by nonuniform flow and movement deformation of bubbles and can effectively extract all collapsed bubbles． Be-sides，it achieves not only a better detection accuracy than that of existing methods，but also robustness of per-formance under different flotation working condition，thus this method meets the on-line detection need of flotation production．


Cerebral Infarction Image Segmentation Based on Active Contour Model



LI Zhi, CHEN Yehang, FENG Bao, et al

2020, 48(5):  102-111,124.  doi:10.12141/j.issn.1000-565X.190594

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Segmentation of cerebral infarction focus is an important pre-processing step to assess functional injury of brain． To solve the low accuracy segmentation problem caused by blurred boundaries，irregular shapes and in-homogeneous intensities of cerebral infarctionin the image of diffusion weighted imaging (DWI)，a segmentation method of active contour model based on fuzzy speed function was proposed． Firstly，the Bayesian probability in the wavelet transform domain was used to obtain the initial contour，according to which the real boundary of cere-bral infarction focus can be quickly located，which may improve the segmentation accuracy of the model． Second-ly，the local entropy of the image was introduced into the active contour model． The local entropy of the image can represent water molecule distribution differences in DWI image，thud solve the problems of inhomogeneous intensities and noise interference to a certain extent． Thirdly，according to the fuzzy characteristics of the cerebral infarction fo-cus，a fuzzy clustering algorithm was proposed to calculate the fuzzy membership degree in the fuzzy speed function by combining the local entropy characteristics and gray-scale characteristics of the image，so as to further strengthen
the distinction between the cerebral infarction focus and the normal tissue． Finally，the fuzzy speed function was incor-porated into the active contour model to construct the energy function． The evolution of the contour curve was stopped at the fuzzy boundary of cerebral infarction focus，so that the segmentation of icerebral infarction was realized． The experi-ment results show that the proposed model can achieve accurate segmentation of icerebral infarction focus．


Mechanical Engineering

Numerical Simulation of an Oil Cooler Based on Multi-Scale Method



SU Fenghua FENG Wenying YUAN Xi

2020, 48(5):  112-117.  doi:10.12141/j.issn.1000-565X.190809

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The pressure drop and heat transfer performance of an oil cooler were simulated on Ansys Fluent with the multi-scale method． In order to improve the simulation accuracy，the heat flux equation of the fins at arbitrary coordinates was established according to the simulation data of the micro-scale model in the oil cooler． The simula-tion conditions were 0. 001、0. 1、0. 2 and 0. 3 m/s on the hot side，and 0. 1、0. 2、0. 3 and 0. 4 m/s on the cold side，respectively． On that basis，the momentum source term equation and the heat flux equation were calcu-lated with the micro-scale model data． The pressure drop and heat transfer performance of the oil cooler were simu-lated under the condition that the mass flow rate on the hot side was 0. 04、0. 08、0. 12、0. 16 kg/s，respectively and the volume flow rate on the cold side was 5 × 10^-4 m³ /s． The research shows that the simulation data is in good agreement with the experimental data，and the relative error is within 10%． The accuracy of the multi-scale simulation method can meet the requirements of general engineering applications．


Study on the Impact Resistance of Shot-Cut Carbon Fiber Reinforced Nylon 66 Sheets 



HUANG Zhenyuan, CHENG Bin, ZHAO Yameng, et al

2020, 48(5):  118-124.  doi:10.12141/j.issn.1000-565X.190367

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Carbon fiber reinforced plastics is a kind of high-quality lightweight materials emerged in recent years．They are widely used in the shell parts of the automotive，electronics，electrical appliances and other industries．These parts often have the risk of being hit or dropped in the process of use，therefore high impact resistance is re-quired． In order to deepen the understanding of the impact resistance of short-cut carbon fiber reinforced plastics，the drop impact test was carried out on short-cut carbon fiber reinforced PA66 sheets． The UT ultrasonic morpholo-gy test and SEM cross-section topography test were performed on the damaged fracture． What's more，the effect of carbon fiber content on the damage behavior and impact resistance of plastic sheets was analyzed by comparing the plate impact failure mode and the displacement-impact force curve． The results show that，in addition to the frac-ture and crack expansion of the plastic matrix，the fiber pull-out and fiber fracture occur in the short-cut carbon fi-ber reinforced PA66 sheets． With the increase of carbon fiber content，the impact damage area and crack number
of the plastic plate are notably reduced，The specific energy absorption and impact resistance of the material are both significantly improved．


Amplitude Filter Characteristics of PCA and Its Application in Feature Extraction of Rotor 



GUO Mingjun, LI Weiguang, YANG Qijiang, et al

2020, 48(5):  125-133.  doi:10.12141/j.issn.1000-565X.190511

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To solve the problem of selecting effective eigenvalues，the number law of effective eigenvalues was de-duced theoretically． That is，one frequency corresponds to two eigenvalues． The order rule of eigenvalues was de-duced as well． That is，the larger the amplitude of signal is，the larger the corresponding two eigenvalues are．The above two properties were collectively referred as amplitude filter characteristics of principal component analysis (PCA-AF)，and a novel signal separation algorithm based on this characteristic was proposed． Through the analy-sis of simulation signal and the actual rotor signal，the effectiveness of the algorithm for signal separation was veri-fied． Ｒesearch results show that the algorithm has excellent advantage in both extracting multiple and single fre-quency components，and the purified signal does not contain redundant components，nor does phase deviation oc-cur． Finally，the proposed algorithm was applied to purify rotor axis orbit of large sliding bearing test bed，and the misalignment fault of the rotor was identified successfully．


Optimization Design of Vibration Reduction for Hypoid Gears with Ease-Off Flank Modification 



JIANG Jinke LIU Zhao PENG Xianlong

2020, 48(5):  134-141,148.  doi:10.12141/j.issn.1000-565X.190829

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An optimization design method of vibration reduction for ease-off modification based hypoid gears was proposed to improve dynamic performances of automobile drive pinion axle． The modified pinion were represented by a sum of two vector functions determining the tooth of conjugate and the pinion normal ease-off deviations ，which were expressed by both predesigned transmission error function and tooth profile modification curves． Mes-hing stiffness was obtained with tooth contact analysis (TCA) and loaded tooth contact analysis (LTCA)． Based on force analysis of the meshing position，the bending-torsional-axial coupling dynamic lumped mass model for hy-poid gears was established，and the vibration response of the system was obtained by solving the differential equa-tion of motion with numerical method． The best ease-off deviations were determined by a optimizing minimal mean square value of normal vibration． Besides，influences of stiffness curve shape and amplitude caused by modifica-tion on the dynamic performance of the system were explored． A numerical example shows that excessive modifica-tion leads to decrease of meshing stiffness，which are responsible for the increase of normal vibration． In case of a little differences in value of average meshing stiffness for the modified tooth surfaces，the shape is more sensitive to vibration than the amplitude for stiffness curve． After the optimal ease-off modification，the vibration of system is obviously reduced． Besides，the average meshing stiffness decreases a little and main frequency in the stiffness curve is meshing frequency，and there is no frequency doubling component． When the amplitude of load transmis-sion error (ALTE) decreases and the high frequency component in the curve increases，the vibration may not be reduced，and ALTE can basically reflect the variation tendency of vibration with loads．


PID Position Control of Pneumatic Muscle Actuator Based on RBF Neural Network 



LIU Kai, CHEN Yining, WU Yang, et al

2020, 48(5):  142-148.  doi:10.12141/j.issn.1000-565X.190253

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The static test platform of pneumatic artificial muscle was built，and a series of measurement tests were carried out under pressure of 0. 1 ～ 0. 8 MPa to analyze the characteristics of pneumatic artificial muscle． The mathematical model，which was built based on the theoretical model and test data，shows a high accuracy of solu-tion． In consideration of the influence of external load，gas pressure and system friction on the mathematical mod-el，a PID control strategy based on ＲBF network was designed with the fast learning ability of ＲBF network． Un-der the condition of external load F = 50 ～ 200 N，the dynamic test platform was built and a number of position control tests were implemented． The results show that the traditional PID control strategy can only achieve better control accuracy within a certain range of external loads，while the proposed strategy is able to adjust the PID pa-rameters adaptively． Moreover，the proposed PID control strategy has the advantages of higher response speed，shorter adjustment time and smaller overshoot，and it can better compensate the mathematical model error and a-chieve higher control accuracy．