Abstract:Coriolis mass flowmeter is one of the most widely used and fastest growing flowmeters. Digital signal processing technology is the core of Coriolis mass flowmeter and it directly determines the measurement accuracy, measurement stability and etc.. The mathematical model of sensor output signal is the basis of signal processing. Scholars at home and abroad have proposed many signal processing methods for Coriolis mass flowmeter. But there is a lack of comparison and evaluation for these signal processing methods based on different mathematical models and different applications. Therefore, the advantages and disadvantages of different signal processing methods are analyzed according to their feature extraction principles. The calculation accuracy, response rate, convergence, antijamming capability and sensitivity of different signal processing methods are compared and evaluated according to random walk model of single flow, mutant signal model of batch flow and ARMA signal model of gasliquid twophase flow. The optimized signal processing methods are determined for signal flow measurement, batch flow measurement and gasliquid twophase flow measurement to solve key technical issues.

Abstract:Railway clearance intrusion detection is critical to the safety of highspeed railway. The foreign object intrusion detection based on 3D laser point cloud segmentation, classification and recognition has the merits of accuracy and intuition, and has broad application prospects in the monitoring of railway key regions such as tunnel entrance and platform. In this paper, an equipment is designed, which drives the 2D laser radar to implement pitching movement and acquires the 3D point cloud of railway scene. Based on the normal consistency principle, the region growing segmentation algorithm is proposed to solve the over segmentation and under segmentation problems caused by Euclidean cluster segmentation and RANSAC segmentation methods. Aiming at the segmented single object point cloud, the Viewpoint Feature Histogram (VFH) is used to extract the 3D point cloud features of different objects; then, based on the VFHs of different objects kdimensional (KD) tree is built, and the closest point searching algorithm is adopted to achieve the classification recognition of single object point cloud. The result of the classification experiment on the typical objects in railway scene shows that the classification recognition accuracy of the proposed algorithm for the typical objects in railway scene is higher than 90%.

Abstract:The wireless signal of wireless local area network is unstable in the indoor environment, and the traditional support vector regression (SVR) based positioning method may lead to the reduction of the correlation between the position coordinates and signal strength. Thus, this paper proposes an improved support vector regression (ISVR) based indoor positioning method. Firstly, the logarithmic processing is conducted on the received signal strength (RSS) to make it more consistent with the normal distribution, and then the Gaussian filter is used to filter the small probability of fingerprints before building the fingerprint database. Secondly, in order to reduce the error of constructing X and Y coordinate model separately, a calibration coordinate z=x·y is trained at the training stage, which can improve the correlation relationship between RSS and XY position information. Finally, the optimal position coordinates are obtained by weighted inverse K nearest neighbor (WIKNN) method. The experimental results show that the proposed algorithm can reduce the noise caused by the complicated environment in the room, and has higher positioning accuracy than the traditional support vector regression algorithm.

Abstract:Due to nonlinearity, system temperature drift and other uncertainties of PZT (PbZrTiO3), there exists uncertainty for the position of AFM (Atomic Force Microscopy) tip in the task space. It seriously affects the observation and operation efficiency of AFM tip. Thus, to reduce the uncertainty of tip position, and achieve precise positioning becomes an urgent issue to be solved. Firstly, this work represents the uncertainties of tip position in the task space by using the probability distribution. Then, tip motion model is established, and local scan based observation model is combined to estimate optimal tip position by using the Kalman filter. In addition, a model parameter calibration scheme is designed to implement the proposed method. The validity and feasibility of the algorithm are verified by the simulation and experimental results. AFM tip precise positioning can be realized in the task space, and the efficiency of nanomanipulation can be improved.

Abstract:Traditionally, the flow cytometry data is analyzed manually, which is inefficient and depends on expert experiences. In recent years, a lot of automatic cluster algorithms have been proposed. However, the clustering performance is not satisfied for sparse data with a random distribution. Therefore, this paper presents an automatic clustering method based on densitydistance center for tmixture model algorithm in flow cytometry data, which is suitable for rare samples. The proposed method finds the center of each group by densitydistance center algorithm and uses it as the initial value of tmixture model to estimate the sample data by maximum likelihood estimation. Compared with the classical algorithm, the result shows that the tmixture model based on densitydistance center has better stability and reliability, and can better fit small or mixed samples.

Abstract:Cracks of girth welds of longdistance oil and gas pipeline bring extremely harm to the pipeline safety, and most of accidents caused by pipeline defects occurred at pipeline welds. So far non destructive testing (NDT) is a common method for predicting potential risk and ensuring the safe operation of pipeline, but traditional NDT methods can’t effectively identify the defects lying in girth welds or other complex surface. In order to overcome the disadvantages of traditional methods, an embedded eddy current testing system is presented based on image processing and neural network. Hough transform and contour extraction are used to extract the features from 2D impedance image composed of eddy current signals. Features with good classification characteristics are selected by the within class scatter matrix to train neural network based on FPGA speeding up. Automatic cracks of girth welds classification and identification is realized with a heavy weld noise floor. Experimental results show that this system can effectively identify the defect signals lying in weld of the cylinder or other complex surface. The accuracy of the system is as high as 92%, and has lower power consumption and smaller size, which is suitable for pipeline inner inspection.

Abstract:In the singlepath pointdiffraction threedimensional measurement system with only one fiber pair, the measurement accuracy in the lateral direction parallel to the fringle direction is poor. To solve this problem, a dualpath pointdiffraction interference system is proposed to enhance the accurate threedimensional measurement in this study. The influence of pointdiffraction wavefront error, structural layout of measuring probe and threedimensional iterative reconstruction algorithm on the threedimensional measurement accuracy is analyzed. Based on the analysis, the optimal system parameters (e.g., pointdiffraction source structure and structural layout of probe) are determined. The experimental results show that the accuracy of the singlepath pointdiffraction interference system for threedimensional measurement in the x and y directions are in the order of submicrons and microns, respectively. In comparison, the dualpath pointdiffraction interference system can reach the order of submicrons at three directrions. The feasibility and accuracy of the proposed system are verified. It provides a feasible method for the measurement threedimensional displacement and size without guide rail.

Abstract:Star sensor is a high precision attitude measurement instrument widely used in spacecraft. The star sensor’ calibration is very essential for the high precision measurement of star sensor. In order to improve the overall accuracy of the star sensor, a simulation analysis is carried out for the traditional star sensor calibration method. The model parameters are difficult to decouple for the traditional star sensor calibration. To solve this issue, a direct mapping calibration method is proposed in which the focal length, imaging plane tilt and distortion, etc. as a whole parameter are calibrated. This simple method can achieve higher accuracy, which avoids the shortcomings caused by the error analysis of the traditional method. Experimental results show that the calibration method fully meets the system requirements of 2″.

Abstract:A threedimensional (3D) target for point clouds stitching with regular hexagonal prism shape is designed, and the 6 chessboard corners on the six sides of the target are used as the global control points. Based on closerange photogrammetry, six element models of the 3D target are built. Through calculating the relative positions among camera stations in every model, the local coordinates of the chessboard corners in related model are derived. Taking common chessboard as the medium, the transformation relationship of coordinate systems for the neighboring element models is determined. The global coordinate system is built on chessboard number 1, and the homography matrix between the chessboard plane and its image plane is derived, so that the transformation relationship between global coordinate system and the local coordinate system of the element model, in which the chessboard number 1 is located, is determined. Then, the transformation relationship between the global coordinate system and the local coordinate system of each element model is derived one by one; and the global coordinates of all target corners are calculated. Afterwards, the SBA (sparse bundle adjustment) algorithm is used to obtain the accurate values. Taking the distances between the chessboard corners on glass surface as the evaluation index, the stitching precision is better than 0.15 mm/m. The stitching experiment based on the 3D target for stitching shows that the local point clouds of the four subarea on the solid model surfaces can be precisely stitched into a whole point cloud. Compared with the stitching methods based on global control points and plane target, the proposed method has higher stitching precision.

Abstract:The existing commercial rheometer cannot satisfy the demand of the high shear rate and stress data of Magnetorheological glue. To solve this problem, a testing device with airtight cylinder shear mode is designed to measure the parameters of Magnetorheological Glues in this study. Based on the overall structural design, the relationship of the exciting current and the magnetic field is obtained by establishing the analytical model of magnetic circuit in shear channel. The relationship is verified by the finite element simulation. Considering the tilt between the rotor and outer cylinder, the torque transmission mechanical model is proposed to get the theoretical relationship between the incline angle and the error of torque transmission. The prototype of testing device is fabricated and the tests for Magnetorheological glue are executed. The experimental data by testing device agree with those by Anton Paar rheometer at the low shear rates. It shows that the test device can reach the measurement with high shear rate of 25 000 s-1 and high shear stress of 200 kPa.

Abstract:Because of the data lost and gross error of ultra wideband (UWB) positioning system in a complex environment, the tracking accuracy of SINS/UWB integrated positioning system is seriously decreased. Aimed at above problem, this paper proposes an SINS/UWB integrated positioning method based on fault tolerant detection for UWB. Firstly, the stationary state detection model is built with measurement of SINS using the Median filter. Moreover, the measured bias of SINS can be calibrated with Least Square algorithm for the stationary state. Secondly, the fault tolerant judgement model is used to detect the UWB, which includes the measured data lost and gross position error caused by None Line of Sight and interference signal. The fault tolerant integrated positioning system can be achieved by Kalman Filter using detected positioning results of UWB. Finally, some experiments are conducted to evaluate the proposed method using experimental platform of SINS/UWB integrated positioning system. The experimental results show the fault tolerant integrated positioning system can effectively detect the data lost and gross error for UWB, meanwhile, the fault tolerant positioning system can guarentee high tracking accuracy for a duration time of 6s for UWB inaccurate state.

Abstract:The rocker flap wavemaker method is taken as an example to derive the wavemaker equation and the waveabsorber equation. Then, the wave parameters are linked to the movement characteristics of wavemaker plate. The verticalplate wavemaker model and rockerflap wavemaker model are designed to achieve the numerical simulation with the Fluent software. In the simulation, the UDF is used to control the movement of wavemaker plate and additional momentum source is used near the wall to absorb wave. The advantages and disadvantages of the two methods are anaylzied. The verticalplate wavemaker method is suitable for small wave and has no special requirement for power source, while the rockerflap wavemaker method is suitable for medium wave and the generated wave is better. According to the simulated data, the physical prototype is designed and manufactured, the wave height is measured in the experiments. The waver generator design method based on the numerical simulation can identify the wavemaker type and key parameters quickly to shorten the design cycle and reduce the development costs, which has important reference significance in developing novel wave generator.

Abstract:A cascaded fiber FabryPerot (FP) cavity fabricated by femtosecond laser with fiber Bragg grating (FBG) and its sensing characterization has been proposed and its temperature and strain sensing characterization has been studied. During two hours of stability test, the maximum FBG wavelength shift is 0.009 nm, and the maximum FBG power drift is 0.015 dB; the maximum FP cavity wavelength shift is 0.018 nm, and the maximum FP cavity power drift is 0.072 dB. When the strain is varying from 0 με to 450 με then back to 0 με, the FBG wavelength peak is shifting towards right then left with the wavelength shift 0.530 4 nm, and the strain sensitivity is 1.17 pm/με with linearity higher than 0.99; the FP cavity wavelength shift 0.4911nm, and the strain sensitivity is 1.10 pm/με with linearity higher than 0.90. When the temperature is varying from 50℃ to 200℃ then back to 50℃, the FBG wavelength peak is shifting towards right then left with the wavelength shift 1.418nm, and the temperature sensitivity is 10.09 pm/℃ with linearity higher than 0.95; the FP cavity wavelength shift 1.578 nm, and the strain sensitivity is 10.53 pm/℃ with linearity higher than 0.98. This paper provides not only effective method to solve the problem of single fiber for double parameter measurement, but also reference value for the measurement of multi parameters coupling and decoupling in complex environment.

Abstract:This paper studies the optimal placement problem of biaxial acceleration sensor used for structural vibration measurement of transmission tower. On the basis of TMAC method, a novel method called Redundancy Reduced Biaxial Modal Assurance Criterion (RRBMAC) method is proposed to realize the optimal placement of biaxial acceleration sensor. The method uses improved twodimension column pivot QR factorization to gain initial sensor positions. The objective function is established based on the maximum value of nondiagonal element in BMAC matrix and measurement point redundancy, and optimization is carried out. EFI2 method and RRBMAC method were adopted to conduct the optimal sensor placement of a steel tube tower. Modal Assurance Criterion and Maximum Singular Value Decomposition Ratio along two horizontal directions were adopted to evaluate the achieved sensor placement scheme. The results show that the optimization effects of the two methods both firstly increase with the number of the sensors, and then tend to stable. RRBMAC method has better placement effects than EFI2 method and RRBMAC method can obtain pretty good optimization capability even when the number of sensors is few. In addition, the two methods were used to carry out the optimal sensor placement of a lattice transmission tower, and the comparison and analysis results show that the RRBMAC method can obtain better placement scheme. The optimal method should be chosen according to the number of sensors together with the focal point of the test. For different number of sensors, the optimal sensor placement method and some sensor placement schemes are presented. Windinduced vibration response experiment on the tower was carried out using the optimized sensor placement scheme, and NExTERA method is adopted to identify the natural frequencies and damping coefficients. Compared with the modal analysis results, the results show that the NExTERA method can extract accurate frequency results.

Abstract:The traditional precise position sensor is susceptible to electromagnetic interference and poor compatibility of composite materials under complicated conditions. A distributed position and pressure doubleparameter sensor is proposed based on long chirped fiber grating. A doubleparameter sensing model of long chirped fiber grating is established, and the theoretical model of doubleparameter sensor based on long chirped fiber grating is validated by numerical simulation. A doubleparameter sensing system for long chirped fiber gratings is developed. The experimental results show that the sensor has a spatial resolution of 50 μm and a linearity of 99.99% for the position measurement in the full scale range. This sensor also has a sensitivity coefficient of 0.003 399 dB/N and a linearity of 99.8% for the transverse force. This sensor can be applied to precise lateral force and location measurement in complex environment.

Abstract:In order to apply TimeGrating sensors to the high speed fields, a novel angle measurement system is designed. This system can achieve dynamic measurement and reduce costs compared with the conventional measuring system. Firstly, optimized coordinate rotation digital computer (CORDIC) algorithm is utilized for rough angle calculation. Then, a high accuracy compensation algorithm is proposed to realize precise angle calculation, considering linear relationship when the angle is close to zero. This method not only reduces the number of iterations, but also achieves higher output accuracy and high realtime performance. Finally, the measurement error caused by the algorithm is discussed, and the error of the whole system is traced. With the parasitic time grating angular displacement sensor as the carrier, by adjusting the sensor input and using the oversampling of highspeed Analog Digital (AD), the whole solution system is implemented and a testing platform is built. Experimental results indicate that the measured precision of the system is below 10″when the signal of sensor has been calibrated, and can satisfy the dynamic measurement requirements.

Abstract:In order to improve axial resolution of the confocal sensor and realize high accuracy measurement of microtopography, the splitpupil differential confocal sensing technique is proposed. The key parameter optimization theory is further studied, and a dividedaperture differential confocal microscopic sensor with optimal theoretical parameters is developed. The developed sensor combines dividedaperture differential confocal microscopy and virtual pinholes based on editable detection device. The offset of the detection area can bring the phase offset of the axial characteristic curve in the dividedaperture confocal microscopy. Two virtual pinholes are set symmetrically on the detection surface in a specific direction, whose responses are obtained and differentially processed to achieve high axial resolution and high positioning accuracy measurement. The developed sensor are tested The axial response, nonlinear property of the developed sensor are evaluated and the actual sample is measured. The axial relative displacement measurement formula is obtained. Experimental results indicate that the axial resolution of the developed sensor is 5 nm and the lateral resolution is 0.82 μm, which can provide a new sensing technology and system for the highprecision measurement of the threedimensional surface of the microstructure.

Abstract:The measurement accuracy of magnetic gradient tensor system is limited by the system errors such as zero drift, sensitivity difference and the three axis nonorthogonality of the magnetic sensor, as well as the misalignment errors among the axis systems of different sensors. In this paper, an error parameter linear model of the planar cross magnetic gradient tensor system is constructed, and a twostep linear calibration method is proposed. Firstly, the linear equation set of single magnetic sensor system error is constructed by using two nonlinear variable conversions, and the error parameters are estimated by least squares method. The actual output of the sensor is calibrated to its ideal orthogonal output. Secondly, the linear equation set of the misalignment errors among the ideal orthogonal axes of the sensors is constructed by using the rotation matrices and the least square solution is obtained. The outputs of sensors are calibrated to the orthogonal coordinate system in reference platform frame. Both processes have no any mathematical simplification. Simulations and experiments show that the proposed twostep linear calibration method of the tensor system is more accurate compared with the conventional linear calibration method neglecting the second or higher order small quantities. The simulated estimation accuracy of the error parameters is better than 93%, the root mean square error of the actually tested total field intensity is less than 13 nT and the root mean square error of the tensor components is less than 90 nT/m in the experiments after calibration.

Abstract:To deal with the long delayed control process of dissolved oxygen in sewage, a control strategy is proposed by combining directly predicting variables based on curve fitting and directly searching for optimization control variables. This proposed method uses a least square algorithm to fit the online data and obtains the predictive values after τ time delay. An optimization method based on the golden section points is used to determine the boundary of the target control variables. The search interval length is gradually reduced till the target control target is reached. Simulation and experimental results show that the proposed control strategy is more effective and efficient for control process of a large time delay. Comparing with traditional method like expert control, the proposed approach can improve convergence accuracy up to 50% and can be used to control the target to ±1%.

Abstract:To relieve the increased damage of inverters and guarantee reliability and safety of PMSMdriven rail vehicles suffering demagnetization fault, this paper presents an advanced lifeextending control strategy through hybrid model. The proposed strategy conducts online remaining flux estimation and offline control law reconfiguration, to decrease the input power of PMSM with demagnetization. It regards PMSMsInverter as a whole electromechanical system for closed loop control to autonomously extend the operation life of inverters. The feasibility and benefit of the life extending control strategy is validated through a simulated experiment of Syntegra PMSM rail vehicle. The simulation results show that accurate monitoring and damage prognosis of demagnetization can be , and the life of inverters is extended effectively without influencing operation performance.

Abstract:Scanning ion conductance microscopy (SICM) can be used to obtain the surface topography of the sample under noncontact conditions. It can realize the nondestructive imaging of soft samples, e.g., living cells in physiological liquid environment. However, there is smearing phenomenon in the SICM image when using the continuous feedbackcontrol scanning mode which is found through a large number of experimental results. It causes the image distortion and limits the scan speed. To solve this problem, the SICM imaging principle is analyzed. It is concluded that the highly nonlinearity of the approach curve is the main reason for this phenomenon, and an adaptive control method based on currenterror compensation model for SICM is proposed in this study. The main idea is to establish a currenterror compensation model, predict the current scanning point position by using the scanning data of the last line as the prior knowledge, and then put it into the compensation model to calculate the new currenterror as the system controlled variable. Finally, the performance of scan images for the standard grating under the new and old control algorithms is compared. The experimental results show that the new algorithm can effectively solve the smearing phenomenon at a certain degree of scanning speed and significantly reduce the image distortion. It provides an effective technical method to improve the image quality and imaging speed of SICM system.

Abstract:Aiming at the characteristics of the kinematic model of nonholonomic vehicle, considering that the interaction relationships among the vehicles are local, a distributed formation control algorithm for nonholonomic vehicles based on leaderfollower is proposed in this paper. Firstly, a distributed estimation strategy is proposed, which estimates the states, including the position, orientation, and linear velocity of the (virtual) leader for each follower vehicle. Then, a formation control algorithm is designed based on the tracking error of each follower vehicle. An asymptotic stability and convergence analyses of the algorithm are performed using Lyapunov tools. Finally, the visual positioning and control experiment platform of multiple vehicles was constructed; and simulation and experiment results verify the effectiveness of the proposed algorithm.

Abstract:River surface imaging velocimetry is a nonintrusive flow measurement technology, in which the flow field calibration mainly uses the Direct Linear Transform (DLT) method. Since DLT is greatly limited by the quantity, distribution and accuracy of ground control points (GCPs) set on the river banks, the current measurement systems cannot layout fast and safely under complex field conditions. To handle this problem, a flow field calibration method based on ObjectImage Scaling (OIS) is proposed. An imaging model of variableheight plane under oblique angle is built by introducing the tilt of camera and variation of water level. Then, a “pointsdistance” transformation between image plane and river surface is derived. Finally, a measuring device assisted by a laser range finder is designed and calibrated to obtain the model parameters. Experimental results show that the accuracy of OIS is close to the DLT, and no control points are needed to be deployed or surveyed with a total station, which significantly improves the efficiency and security of the field work. This study is expected to provide theoretical and technical support for the design of new integrated optical instrument for river flow measurement.

Abstract:How to reduce the difference between segmentation result and practical geographical object is a difficult problem faced by highresolution remote sensing image segmentation currently. Aiming at this issue, in this paper a new OC (Object Confidence) index is constructed to measure the matching degree between any region and geographical object, and a multiscale segmentation algorithm facing to geographical objects is proposed. This algorithm mainly contains two steps: firstly, this algorithm establishes an initial seed regional set through conducting over segmentation to the image and determines the scale parameter set; secondly, this algorithm guides the process of multiscale region merging through tracking the interscale change of OC index, and makes the region merging result gradually approach to practical geographical object. The multigroup experiments indicate that the proposed algorithm can obviously improve the oversegmentation and insufficientsegmentation problems, and identify the complete outlines of buildings, roads as well as other geographical objects accurately. The proposed algorithm is obviously superior to the commercial software eCongnition and traditional multiscale segmentation algorithm in both qualitative analysis and quantitative precision evaluation.

Abstract:Electromagnetic tomography (EMT) technology is used to realize the visualization of metal defects, which overcomes the lack of visualization of traditional testing technology. Firstly, a new planar sensor is designed. Secondly, according to the sparsity of defect distribution, the l1 regularized sparse imaging algorithm is proposed. The l1 regularization algorithm effectively overcomes the excessive smooth problem associated with traditional l2 regularization algorithm, whose imaging results are more accurate. Finally, in order to further prove the superiority of the new algorithm compared with l2 regularization algorithm, the simulation and experiment are conducted. The results show that sparse imaging algorithm can effectively improve the quality and accuracy of the defects images.

Abstract:A wheel model identification algorithm based on Shape Recognition and Texture Filtering is proposed. Firstly, a spokes shape of a standard template is defined, and its edge map is obtained. Taking the template as a window to shift matching at an edge detection figure of the identified image, the minimum distance between template and region of interest of the identified image is calculated. If the minimum distance is less than the specific threshold, a shape consistent with the template is determined. Then, Random Walk Operator is used to traverse the identified image and obtain the Wander Histogram. Comparing this histogram with the Wander Histogram of template wheel, the texture deviation degree of two image is calculated, and the right wheel model is determined. Finally, the experimental results show this algorithm has the advantages of noncontact, flexibility and accuracy, and has good robustness for the shape recognition with heavy disturbance.

Abstract:The ratio and the diameter of artery/vein of the retinal can reflect the risk of stroke of hypertension, thus, quantitative analysis of the diameter of the vessel can contribute to risk assessment and prevention of the disease. A artery/vein automatic classification method in Retinal Images and Vessel Diameter Measurement are introduced in this paper. Firstly, the vessel centerline is obtained after segmenting the retinal vessel. Secondly, different channel components in different color spaces are selected, the eigenvectors of centerline pixels, vessel pixels. vessel widths and central light reflection are defined. Kmeans clustering algorithm is adopted to classify the artery/vein in the measurement region of interest. Finally, the distribution curve of the vessel cross section is fitted using the Gaussian curve and the width of the artery/vein can be obtained according to Half Height Full Width. Experiments with Review public database and Drive public database prove the effectiveness of the proposed method.

Abstract:Brake pad dimension detection is one of the important indices of brake pad quality. In order to quickly and comprehensively detect the dimension of the brake pad, this paper presents a comprehensive brake pad dimension detection method based on tolerance design principle and image processing. Firstly, according to the requirements of the design drawings, the dimension tolerance design principle is used to reversely design the brake pad allowable dimension tolerance control zone, which is taken as the comprehensive dimension test standard template. Secondly, the CCD camera is used to acquire the image of the brake pad to be tested, which is then filtered, processed with binarization; a binary image is obtained and the minimum circumscribed rectangle optimization algorithm is used to determine the scaling factor, and the actual image the same as the standard template in pixel scale is obtained. Finally, at the midpoint of the line connecting two cycle center coordinates of the actual image and standard template, two images with same size are cut out. Edge detection is performed on the actual image to get the actual contour image, then the actual contour image and the standard template are added up, and then from the difference of the numbers of the white pixels for the added image and standard template, the detection result is obtained．The experiment result shows that the detection accuracy can reach 1 pixel, the detection speed reaches 1 piece per 5 seconds, and the proposed method can detect weather all the dimensions of the brake pad are qualified.

Abstract:In order to solve the problem of mutual restriction between high spatial resolution and large field of view of industrial cameras prominently protruded in the visual measurement of finepitch gear, this paper studies on the subpixel image registration method for finepitch gear that has strong foregroundbackground contrast, insufficient local contrast and large area of the same color under rimming light condition. Aiming at the problem of less feature points and low correct matching rate in the image registration process based on feature points in finepitch gear image registration, the registration process suitable for finepitch gear image is described in this paper, the global histogram equalization is introduced to improve image contrast, enrich grey level and enhance the feature information in dark part of the image, so that the number of feature points and correct matching rate are improved. In order to overcome the deficiency of incorrect threshold setting, parameter adjustment difficulty and model nonuniqueness of traditional matching pair purification algorithm, combining with 2σ criterion, the global selfadaptive parameter matching point pair purification algorithm is put forward, which not only ensures the uniqueness of the purification result, but also adjust the judgment threshold adaptively to avoid artificial error and ensure the repeatability of result. Experiment results show that the number of feature points and correct matching rate are greatly increased when the image is preprocessing with the method described in this paper. Besides, the registration result measured by the average of translation amount purified with the method described in this paper outperforms that of the traditional method in correctness and precision. Aiming at the finepitch gear image under rimming light condition, the registration precision is better than 0.083 pixel, which has great practical application value for the visual measurement of finepitch gear.

Abstract:The frequency of vessel collision is defined as the product of vessel traffic conflicts and causation factors. In the previous studies, the dynamic effects of influencing factors on the ship domain were usually ignored. Using the traffic conflict technique, this study first proposes a dynamic ship domain model and then develops a model to estimate the vessel collision frequency in open seas. Model results show that the most collision risky areas are Niusha Island(24°46.8′N～25°30.0′N), Xiongdi Islet(23°22.8′N～25°49.2′N) and Xiamen Bay Waters(24°08.4′N～24°33.6′N). The collision frequency of the Taiwan Strait is 5.068 7/year, which is very close to the mean value of 4.866 7/year based on 15 years’ historical accident data. Studies indicate that the crossing collision conflict is the major collision type in the Taiwan Strait. In addition, the vessel collision frequency during the nighttime period is slightly bigger than the daylight period. This work not only provides a new method to estimate collision frequency, but also provides a theoretical basis for the quantitative risk assessment of vessel collision in the future.

Abstract:This paper presents the design and development of a crossaxis chromatograph. Firstly, the suitable mechanical structure is designed considering design requirements. The kinematics analysis is carried out to obtain the driving torque by the theorem of momentum moment. Secondly, the modal analysis is carried out in order to obtain the weak link of the structure. Finally, the structure of weak link is optimized to develop the prototype. The separation efficiency and influencing factors of the prototype are tested by experiments. The results show that, with the increase of the rotational speed in a certain range, the retention rate of stationary phase of the prototype increases, and the separation efficiency also increases. When the speed of the prototype reaches 800 r/min, the retention rate of stationary phase is the largest. The retention rate of stationary phase decreases when the speed exceeds 800 r/min, then the separation efficiency decreases. When the speed of the chromatograph keeps constant, the velocity of liquid in the chromatograph is greater and the retention rate of stationary phase is lower.