Abstract:In medical field, the mobile rehabilitation exoskeleton robots arouse wide concern as they can help the paraplegic to regain the ability to walk again. Due to the body specificity of paraplegic patients, as the balance axillary means, crutches are necessary for the paraplegic patients who wear the exoskeleton robot to keep balance. We found that in the case of fixed step length, different support point positions of the crutches have great impact on the gait stable threshold. In the paper, through analyzing the polygon support plane formed when the users wear the exoskeleton robot to walk with crutches, ZMP theory is used to calculate corresponding position of the center of pressure. Thus, the stable threshold expression of quadruped gait is obtained. Based on these, the method of dynamically adjusting step length is proposed, and the fitting surfaces of the crutch support point and step length is obtained, thus the step length can be adjusted properly and in real time. Finally, the gait trajectory is planned using the kinematic model of the exoskeleton robot. A large number of comparison experiments were carried out on the exoskeleton robot developed independently by our team, the results prove that aiming at different crutch support positions, the proposed method can significantly increase the system gait stable threshold and reduce the influence of the crutch position randomness on system stability in each gait cycle.

Abstract:Recent years the study on rehabilitation robotics has become the interdisciplinary research hot spot in medical rehabilitation engineering and robotics fields. In this paper, to improve the interaction capability of rehabilitation training robot, the virtual reality technology and robotics technology are combined together, and the lower limb rehabilitation training robot system based on virtual scenario interaction is studied. The Kinect sensor was used to acquire the human skeleton information, Unity3D game engine and 3D Studio Max software were used to develop the virtual environment for scenario interaction. The gait synchronization control algorithm for the patient and virtual character was designed, and the synchronous interaction in the rehabilitation training process was realized. The experiment results indicate that the gait synchronization control algorithm is effective, humancomputer interaction is friendly. The proposed gait synchronization control algorithm could help and motivate the stroke patients realize active rehabilitation training.

Abstract:With the purpose of releasing the effect of the impulse to the robot system and its motion control for the instant the hydraulically actuated leggedrobot touching down with the dynamic gait, a robot′s compliant touchdown control method based on the joint motion planning is presented. Focusing on the hydraulically actuated singlelegged robot as the research object, two ways of robot compliant touchdown is obtained by analyzing the endeffector's impulse, which selects the proper touchdown posture of the robot and reduces the endeffector's velocity before touching down the ground. Furthermore, the joint motion trajectory on both of the flight phase and stance phase are planned. The former is based on the cosine velocity curve and the latter is based on the cosine function curve. Afterwards, the method is applied to the hopping control of the hydraulically actuated singlelegged robot emulated on MATLAB/Simulink and then to the robot prototype. Both of the emulated and experimental results indicate that the pressure impulse in the hip cylinder′s rodless chamber after the robot′s endeffector touching down the ground is eliminated. Experimental results verify that the robot's compliant touchdown control method based on the joint motion planning is reasonable.

Abstract:In the created robot drama, a turtle robot plays an important role. The coordinated quadrupedal gait is the key factor to complete the its performance on the stage. Through indepth observation of an actual turtle’s movement, we analyzed the characteristics of its gait and summarized the rules of the movement. Then, we proposed a bioinspired coordinated planning method for quadrupedal gait. The analytical inverse kinematics equation was derived, and the trajectory of foot (the end of leg) was also resolved into the motion of each joint of the leg. The generated joint angles were taken as the expected values of joints’ servo controllers. In order to verify the proposed method, a dynamic simulation system based on Webots software was developed and simulation study on typical gaits was performed. Finally, using the manufactured robotic prototype, we completed several experiments on coordinated quadrupedal gait planning. The results showed that the proposed method is effective for robotic drama performance.

Abstract:Because of the high radiation and complex structure in the nuclear power plant, the operating personnel can be affected by radiations that greatly threaten their physical security and life safety. The reactor multifunction robot for object salvaging underwater is designed to solve this problem. Firstly, the manipulator is modeled with the DH rule, and its forward kinematics formulation, inverse kinematics formulation and singularities of the manipulator are calculated. Considering the comprehensive influence caused by factors such as the water resistance, additional mass force and buoyancy force, dynamic equations of the underwater robot are established, which can describe the complicated dynamic behavior. Finally, an engineering prototype of the third generation of reactor robot is developed. The results of the grabbing test show that the engineering prototype of the reactor multifunction robot for object salvaging underwater realizes the goal of grabbing foreign matters in the nuclear reactor pool.

Abstract:To improve the positional accuracy of the mobile robot at the worksite, the effect of ultrasonic sensor beam angle is analyzed on the basis of considering the incidence angle, and the functional relationship expression of ultrasonic distance measurement is established on regarding the ultrasonic sensor beam angle and the incident angle at the same time. Calibration method of the ultrasonic beam angle is proposed, and the ultrasonic sensor beam angle is obtained through the calibration experiment. It is clearly that the established functional relationship expression of ultrasonic sensor measurement improves the distance measurement precision evidently in the experiment. Based on the proposed expression, three positioning (lateral positioning, front positioning and orientation positioning) methods of the mobile robot are adopted by using two ultrasonic sensor installed on these any single side of robot at the worksite. Finally the method is used in the positioning experiment on the independentlydeveloped mobile robot, and the correctness and effectiveness of the proposed method are verified.

Abstract:Different from the existing researches on target tracking using a fixed motion pattern, an algorithm is proposed for online recognition of human motion patterns with a monocular camera, to develop a human tracking method. First, moving target is detected using visual information and the visual features are extracted. Then, the motion features of target are acquired by depth extraction algorithm of monocular vision. The differences of a couple of successive frames' features are fed into random forest (RF) classifier to recognize human motion patterns online. Finally, different target motion models are chosen online based on classification results and approximate optimal particle filter is used to realize accurate estimation of human’s states. Extensive experimental results demonstrate the effectiveness of the proposed algorithm.

Abstract:A distributed formation control method for cooperative collision avoidance and formation maintenance of multiple mobile miniature robots is presented. Combined with the motion control model of mobile miniature robots, a path planning method is proposed, so that the robots can avoid collision in real time. Utilized the proposed model, a novel controller for formation control is designed by the Lyapunov method, and it can guarantee the trajectory tracking and cooperative collision avoidance within bounded error. The complexity of the formation control is reduced by transforming it into tracking trajectory of the mass center of whole formation, thus it can be better applied to multiple mobile miniature robotwith limited computing resources. The stability and feasibility of the control method are verified by simulation, analysis and comparison, and both the formation control and cooperative collision avoidance are carried out in the practical experiments.The experimental results demonstrate that the method can be applied to the cooperative collision avoidance and formation control of multiple mobile miniature robots effectively.

Abstract:SLAM (simultaneous localization and mapping) is widely used for selflocalization of robot, which is a basis for autonomous navigation of it. In order to autonomously navigate in unknown environments, a robot has to move around and generate the environmental map while localizing itself. However, SLAM in large scale environments is still a challenging research topic, and there is no complete system been reported yet that integrates SLAM and geographic information in such environments. In this paper, we propose an autonomous navigation system consisting of a GIS (Geographic Information System) database, SLAM system, and path planning method. The system is based on the computing capability of the GIS database. It can provide navigation guidance for a robot in a large geographic space. It is highly reusable and extensible. Moreover, the mapping result can serve as the basis of relocalization of a robot in the area even without a GPS sensor. Combining the geographic information and the mapping results of a robot is of great help for the robot to understand the environment, and in the meantime, to enrich the origin geographic information with more details.

Abstract:In order to deal with the collision between the components of the reconfigurable cable-driven parallel robot(RCDPR) and the obstacles in operating environment, a novel collaborative obstacle avoidance method is presented based on critical support lines and multi-finger grasp. Firstly, the general model of RCDPR in complex environment is derived by simplifying the robot structures and obstacles. Based on the model, the collision-free area of the RCDPR is estimated using the topological constraint of robot structure and the critical support lines between obstacles. The collision-free force closure workspace of different types of RCDPRs and obstacle distribution is obtained with convexhull method and convexhull mapping method, respectively. The impact of obstacle distribution and robotic type is analyzed. Then, in terms of a specific trajectory for the end-effector of the RCDPR, the optimal distribution of cables is derived with optimization algorithm. Finally, the verification is conduction the RCDPR prototype. The experimental results indicate that the presented method can effectively prevent the collision during the RCDPR movement.

Abstract:Human beings can accomplish decisionmaking and dexterous manipulation with their complex sensory perception and motor control capabilities. The fusion of visual and auditory feedback together with haptic feedback, enables close resemblance of manipulation in the virtual scenarios with that in the physical world. Further, it is challenging to coordinate the human intervention and the autonomy of the robot in the virtual scenario. Here, a virtual scenario is built up with Unity3D, taking advantages of its powerful rendering capabilities. Then, bidirectional communication between Unity3D and the omega.7 haptic platform is realized. After that, virtual range sensors based on collision detection are designed and implemented for environment perception of the avatar in the virtual scenario. Further, a humanrobot haptic shared control strategy is designed and realized, enabling the avatar to move under the shared control of the dexterous operation by the human and the autonomous algorithms. The control authority can shift smoothly between the human operation and robot autonomy. Thus, a dexterous haptic interaction solution with Unity3D and the omega.7 haptic interface is established, which can find promising applications in rehabilitation, teleoperation, military missions and also the entertainment industry.

Abstract:Malocclusion is currently the most common oral disease. Fixed appliance technology is the effective treatment method for malocclusion, and the key step of fixed appliance technology is the accurate bending of orthodontic archwire. A robot with precise position and posture control ability can realize the bending of orthodontic archwire. And the formed accuracy of orthodontic archwire with robotic bending depends on formed control point planning of orthodontic archwire. Based on the segment orthodontic archwire mathematical model, the finite point extension method is presented to realize the formed control point position planning of orthodontic archwire. The position planning strategy of formed control point of orthodontic archwire is studied. On the basis of the position planning experiments of formed control point of orthodontic archwire, the influence of arcchord difference value on control points number and area error, and the control points number on area error with different arcchord formed area are analyzed. Aiming to the oral parameters of patients, the bending experiments of orthodontic archwire are conducted by using the orthodontic archwire bending robot system. The experimental results verify the effectiveness of the position and angle planning strategy of formed control point of orthodontic archwire.

Abstract:Motion planning is the basis for the motion control. However, motion planning for a cannula flexible needle insertion in the soft tissue is a great challenge. On the one hand, the kinematics of the needle is a nonholonomic motion, and on the other hand, the needle has to steer clear of the anatomical obstacles and sensitive organs to reach the target precisely. By analyzing the deficiency of existing motion planning algorithms, a motion planning algorithm for the cannula flexible needle is proposed based on an improved RapidlyExploring Random Trees (RRT). The GreedyHeuristic strategy is proposed, which is combined with the ReachabilityGuided strategy to improve the conventional RRT. Linear segment is introduced into the planning, and the combination path of the linear and curvilinear segments is adopted. Insertion orientations are taken into account at the same time. Simulations are performed in 2D and 3D environments with obstacles based on the kinematic model of the needle. Results show that the proposed algorithm yields superior results compared with the commonly used algorithm in terms of computational speed, convergence, form of path and robustness of searching ability. These superiorities potentially provide the basis for the upcoming realtime motion planning. At last, the experiment for the planned path is carried, and experimental results show that experimental paths agree with the planned ones very well, which not only proves the validity of the proposed path planning algorithm but also proves the feasibility of the planned path.

Abstract:As the population aging is aggravated, the detection and alarm of falls in elderly people are becoming more and more important. In order to improve the accuracy of fall detection, an intelligent fall detection method based on discrete feature is proposed. Through analyzing the human motion data, seven kinds of discrete features of human motion are proposed. A fall detection model based on BP neural network is established. The extracted discrete features are used as the inputs of the fall detection model, and the output of the model is the result of fall detection. Through the learning and training of the model, fall detection is achieved. The method verification and product application results indicate that the intelligent fall detection method based on discrete features can effectively distinguish fall and nonfall, improve the fall detection accuracy and reduce the false alarm rate and missing alarm rate.

Abstract:Driving style evaluation is an important research topic in the field of intelligent transportation, which is usually recognized and classified qualitatively using time or frequency domain analysis methods and lacksobjective, quantitative evaluation system. A quantitative analysis method for driving style of the driver based on phase space reconstruction is proposed. Firstly, the vehicle test data and local neural network are adopted to establish a personalized driver model. Secondly, the personalized driver model is applied to the speed tracking test in normalizeddriving cycle test to achieve the normalization of driving behavior. Finally, the phase space reconstruction of the normalized driving behavior is conducted, a driving style index is proposed based on the correlation dimensionand used for quantitatively evaluating the aggressiveness of the driving behavior. The driving style index is further applied to the recognition of driving styles. Simulation results verify the effectiveness of the proposed method.

Abstract:The classic bowtie filter for CT is used to shape an xray beam and equalize its flux reaching different detector channels. An ideal bowtie filter, dynamic bowtie, could dynamically modulate incoming xray beams with CT scanning as a function of the angle of the xray with respect to a patient to balance the photon flux on a detector array. In addition, the bowtie filter is expected to be able to make the photons data on the detector array uniform in order to compress the dynamic range. Here, an overview of the progress made in the field of dynamic bowtie is presented, and basic principles of dynamic bowtie which are under the attention are introduced. The design theory of the dynamic bowtie for conebeam CT is discussed. In the end, the prospects for developing trends of the dynamic bowtie are proposed.

Abstract:By adopting twosection ERT system, the Gasliquid two phase velocity measurement is tramsformed into time delay estimation, due to the ERT has the advantages of high realtime and nonintrusive measuring. The Gasliquid twophase flow signals are mostly nonstationary, hence, cross correlation analysis with traditional time delay algorithms will bring multimodal function which leeds to a serious deviation of twophase velocity measurement. Aiming to improve measuring accurancy and stability, a novel time delay estimationalgorithm is proposed with the lifting wavelet. Based on reweighting method with mother wavelets, the improved threshold lifting wavelet function removes the noise of the raw signal, and the Morphological Lifting Wavelet is utilized to denoise the lagging correlation between the upstream and downstream for time delay estimation to obtain the accurate velocity result.

Abstract:Crypt texture is an important feature texture on iris surface. For visible light iris image, how to extract the crypt texture fast and accurately without being influenced by the interference factor, such as eyelashes, eyelids, light spot and uneven illumination is still a challenging task. In order to solve this problem, a visible light iris crypt texture detection method based on morphology and support vector machine (SVM) is proposed in this paper. Firstly, the method combining grayscale morphology and twovalue morphology is applied to extract all the target textures in the iris image; and then, the regiongrowing method is used to locate all the target textures and calculate their corresponding feature vectors; at last, SVM and the method defining constraint condition are applied to extract the final crypt textures. Experiment results show that the proposed method can overcome the interference of light spot and etc., and is superior to other methods in terms of crypt texture detection rate.

Abstract:Theoretical and experimental researches are carried out on nondestructive evaluation of mechanical properties of layercoated cylinders, which is of great significance for the surface quality detection and evaluation. In this work, the labdeveloped acoustic microscopy and the linefocus PVDF transducers are applied in the defocusing measurement with different coating thickness. Considering the nonlinear relationship between the propagation path of the surface wave and the defocusing distance, the geometric parameters of the PVDF transducer are related to the defocusing distance and the cylindrical radius. A correlation analysis method is developed based on V(f,z) analysis to extract the dispersion curves. Combined with the characteristicsof wave propagation of coating materials, the acoustic parameters of cylindrical coating materials are inversed by fitting the theoretical curves to the experimental ones, using the particle swarm optimizationbasedsimulated annealing(PSOSA) algorithm. Hence, the elastic constants of coatings are obtained. The experimental results indicate that the measurement results well match the theoretical counterparts, which prove that this method is reliable and accurate. This method provides a powerful technique for the nondestructive evaluation of cylindrical coating materials. Furthermore, it can be a great tool for evaluation of material properties in Surface Engineering.

Abstract:For detection of large structure surface cracks, a positioning method based on image processing technology and coordinate mapping is presented. First, the highest resolution frame is extracted from the sequence images, and the Retinex algorithm is used to compensate the uneven brightness. Second, the landmark image coordinates are mapped to observation coordinates. The mapping relationship between the world coordinate system and the observation coordinate system is calculated. Third, the morphological image processing algorithm is used, such as convex hull, pixels and thinning, to extract crack image coordinates. If there is a new crack, its observation coordinate is mapped to the world coordinate. If there is an old crack, its world coordinate is mapped to the observation coordinate. The observation angle in current observation system is calcualted. The result shows that this method is efficient, accurate and convenient, and the position error is less than 0.07°in 16 seconds.

Abstract:A new method based on Dirichlet Process Mixture Model (DPMM) is proposed for tool wear monitoring and tool wear estimation. This method describes the toolwear process as a wear accumulation process. Thus, the current tool wear is estimated by continuously estimating the wear increments. Firstly, the features are extracted from the raw force signals, and DPMM is used to classify these features automatically without determining the number of states of wear increments. Then, Gibbs sampling method is applied to identify the parameters of DPMM, which constructs the relationship between force signal features and wear increments. Based on the mixture model and online force signals, the wear estimation can be achieved. A practical study demonstrates that the proposed method is capable of selfadaptively learning wear increment states and effectively estimating the continuous tool wear.

Abstract:Health condition monitoring problem of permanent magnet synchronous motor can be treated as a multi parameter identification problem of the permanent magnet synchronous motor. In order to improve the efficiency of system parameter identification and state monitoring, a kind of health condition monitoring method of the permanent magnet synchronous motor is proposed based on the multiagent bat algorithm. The competition and cooperation operation of multiagents enhances the communication of agents, and the ability of global optimization and the dynamic tracking performance of the algorithm is improved. Selfstudy operation can improve the local search ability and the convergence rate of the algorithm. Multiparameter identification results of the permanent magnet synchronous motor show that the multiagent bat algorithm can quickly and efficiently identify parameters of the motor. The task of monitoring and early warning can be implemented for the running permanent magnet synchronous machine according to changed parameters. Compared with the unmodified algorithm, the improved algorithm shows the effectiveness and superior performance.

Abstract:The fluctuations in the unsteady flow channel field can easily affect the efficiency of mass transfer and heat transfer.An experimental system is constructed to carry out 2DPIV measurement of the transient velocity vector field flow of unsteady field. With the experimental system, and the forms of vector field and vorticity distribution at each time are analyzed, and the cycle and frequency of the unsteady flow are obtained. The transient velocity vector field of unsteady flow field is decomposed using Proper Orthogonal Decomposition (POD) technology. According to the energy ratio of various modes , the first 16 modes as dominant modes are selected to represent dominant structure of unsteady flow field, and the first 16 modes coefficient of the POD decomposition are analyzed using power spectrum. The decomposition results show that the low order modes with POD are the fundamental frequency and corresponding frequency multiplication of the unsteady flow field, and the fluctuation mechanism of unsteady flow field is revealed. The fluctuation of the unsteady flow field is caused by some vortexes and cosines wave formed mainstream, the fluctuation frequency of the vortexes and wave mapping of the mainstream maps the dominant low order coefficients of POD.

Abstract:The feature extraction is difficult to conduct for weak vibration signal in strong noise background. Thus, a feature extraction algorithm is proposed based on Improved Dictionary Learning and Shift Invariant Component Filtering(IDLSICF). Firstly, vibration signal is segmented and smoothed to decrease the complexity. Then, improved dictionary learning algorithm as well as efficient coefficient solver is used for constructing adaptive filter based on shift invariant sparse coding. The shift invariant components constructed by dictionary atoms is filtered to obtain optimal basis function for representing inherent signal features. Finally, intensity of characteristic frequency in optimal basis function is utilized for evaluating performance in signal feature extraction. Experiments on both simulation data and practical data demonstrate that the proposed algorithm can realize better performance on feature extraction compared with the uptodate methods and is more feasible for the practical applications.

Abstract:The aging feature quantity of transformer oilpaper insulation system is different under different test methods. Some ambiguity and uncertainties still exist in the comprehensive assessment of complex insulation condition. Thus, the transformer oilpaper insulationcondition assessment model is established based on fuzzygray clustering and comprehensive weight method. Firstly, the aging index hierarchical graph based on multiple test methods is obtained.Usingfuzzt C –means clustering (FCM, Fuzzy cmeans), the four levels of the aging state standard index vector table of oilpaper insulation condition assessment is identified and the threshold of whitening function is determined with the collected transformer insulation aging index data. Secondly, the gray clustering coefficient is calculated by assigning weight to the aging quantity by weighting method combined with subjective and objective sense.Thirdly, a comprehensive assessment model of oilpaper insulation state is built taking the gradeone gray clustering coefficient as the membership matrix of gradetwo fuzzy comprehensive assessment. Finally, the validity and accuracy of new assessment method are verified by examples, which shows a good prospect.

Abstract:There are many kinds of defects in pipelines, which are difficult to detect and of low automatic test capability. aiming at this issue, a new omnidirectional vision inspection method for the morphology defect detection in pipelines is presented in this paper. Firstly, an Omnidirectional Vision Sensor (ODVS) is designed to obtain the omnidirectional texture information of the pipeline interior. Then, an Active Stereo Omnidirectional Vision Sensor (ASODVS) is designed to obtain the depth information of the inner wall of the pipeline quickly with high precision. Finally, by combining these two kinds of ODVS and merging the omnidirectional measured data with the omnidirectional texture data by the software, the functional and structural defects of pipelines can be automatically analyzed and evaluated. Meanwhile the 3D reconstruction of the pipeline can be achieved. The experimental results show that the ASODVS+ODVS designed in this paper can obtain images with texture information and geometry information inside the pipeline in real time. Tthe pipeline robot can be configured to inspect and distinguish the defects, simultaneously reconstruct the pipeline with the robot walking.

Abstract:Based on the nanometer timegrating displacement sensor with double row structure, a novel nanometer timegrating displacement sensor with single row differential structure is proposed in this paper. An alternating electric field with stable motion is constructed to generate a travelling wave signal to overcome the cross interference and installation existing in the double row structure. Differential induction electrodes are employed to pick up the signals, which can effectively eliminate the common mode interference. Micronano fabrication technology is adopted to fabricate a prototype sensor with single row differential structure based on multilayer thin films, and the performance of the prototype sensor is evaluated. The experimental results indicate that the prototype sensor achieves a value of ±150 nm measurement accuracy within 200 mm measuring range. Comparing with the double row nanometer timegrating sensor, the measurement accuracy, signal stability and antiinterference ability of this sensor are greatly improved. In addition, the size of the sensor is reduced while the effective measuring range is extended. Therefore, the novel nanometer timegrating sensor has more application prospects in the process of commercialization.

Abstract:In order to achieve precise trajectory tracking control for a quadrotor in the presence of external disturbances affecting and system model parameter uncertainty, a nonlinear trajectory tracking controller for the quadrotor is designed and verified. In this paper, the mathematical model of the quadrotor considering the actuator characteristics is firstly established and the virtual control is mapped to the motor control. Then, a nonlinear trajectory tracking controller based on integral backstepping method is designed by adding the integral term to the controller, to eliminate the errors caused by the uncertainty of model parameters and external disturbance. The numerical simulation results prove the feasibility of the method. Finally, the designed nonlinear trajectory tracking controller is applied to the QBall2 quadrotor flight test. The flight test results illustrate the effectiveness of the method, in which the tracking control accuracy is improved under the external disturbances and system model parameter uncertainty in the practical environment.

Abstract:Various methods for pressure calibration by dropweight device are discussed in detail. The measurement accuracy of force sensor is easy to be influenced by pretightening force and inertia force. An improved method to enhance the measurement accuracy is proposed. A high precision force sensor is designed based on the structure of the original weight, from which the inertia force correction model of absolute calibration is derived. In further, the model simplification conditions are summarized. Calibration tests are carried out and the experimental results show that traditional installation methods of transition parts connecting and bolt fixing generate additional adverse effects of pretightening force and inertial force. As a result, relatively large error exists during the measurement of impact force between weight and piston rod. In contrast, pressure can be calculated directly by measuring values of force sensor and crosssectional area of piston rod, under the conditions that the mass of weight is far greater than piston rod and high precision of central impact. Compared with the existing quasistatic calibration method, the monitoring accuracy of high pressure is improved larger than 1%, which can be regarded as an effective pressure calibration method.

Abstract:There is a nonlinear relationship between the output of the moisture instrument weighing sensor and the weight of drying objects, and the working environment temperature change will also make sensors’ nonlinear output for the loss on drying method. After analyzing the nonlinear output mechanism of the strain gauge sensor, the paper presents a new weighing sensor’s nonlinear compensation method based on least squares support vector machine (LSSVM) and mutated modified particle swarm optimization (PSO). Firstly, this method uses noise covariance variable kalman filter algorithm to filter data to reduce the noise influence. Then, establishes a regression model based on LSSVM is established for filtered data and working temperature. Finally, a mutated PSO algorithm is applied to optimize the model parameters. The experimental results show that the accuracy of the 220 g/0.001 g moisture instrument with the proposed method is much higher than the national verification regulation standard. Moreover, the model has excellent generalization ability with small samples.

Abstract:To improve the testing efficiency of the IP core in threedimensional networkonchip(3D NoC), research on test scheduling of the 3D NoC under the multiple constraints is conducted. A new method taking the TSV allocation and the IP core test data assignment as two optimization variables respectively, and coevolved them by the discrete particle swarm optimization algorithm is proposed to minimize the test time and fully utilize the limited TSVs under the multiple restrictions such as the limited number of TSVs, power and the constant bandwidth. To enhance the global searching capacity and increase the diversity of population to refine the stagnation phenomenon, strategies of introducing the global suboptimal extreme's influence on the update of particle and adjusting the parameters by selfadaption are designed. Taking ITC'02 test benchmark as the experiment object, simulation results demonstrate that the proposed method can effectively accomplish the placement optimization of TSVs and the allocation of the communication resource under the multiple constraints, and therefore the test time is shortened and the TSVs′ utilization is improved.

Abstract:This paper analyzes the main factors affecting the signal integrity of highspeed data acquisition circuit based on the characteristics and requirements of highfrequency signal test instrument use environment.Aiming at the reflection and crosstalk of highfrequency signal, the signal integrity design is carried out from the multilayer PCB board laminated design, differential signal transmission line serpentine routing and adding impedance matching network, respectively. The network topology model of differential signal transmission line is established, andthe structure and parameters of the impedance matching network are determined through simulation, which reduces the signal reflection and crosstalk caused by transmission line impedance mismatch. The power integrity is analyzed, the circuit ground bounce is reduced with the inner electric layer segmentation and filter capacitor network, and thereby, the system noise of the test instrument is reduced. Finally, test experimentunder simulation environment was conducted, which verifies the signal integrity analysis of highspeed data acquisition circuit; the experiment result shows that with signal integrity design, the antijamming capability of the testinstrument is improved, and the collected data are reliable and effective.